Kang, B.H.[Bong-Hyup],
Jeon, C.W.[Chang-Won],
Han, D.K.[David K.],
Ko, H.S.[Han-Seok],
Adaptive height-modified histogram equalization and chroma correction
in YCbCr color space for fast backlight image compensation,
IVC(29), No. 8, July 2011, pp. 557-568.
Elsevier DOI
1108
Backlight compensation; Image enhancement; Contrast enhancement;
Histogram equalization; Saturation
BibRef
Park, D.[Dubok],
Kim, M.J.[Min-Jae],
Ku, B.[Bonhwa],
Yoon, S.[Sangmin],
Han, D.K.[David K.],
Image enhancement for extremely low light conditions,
AVSS14(307-312)
IEEE DOI
1411
Dynamic range
BibRef
Jung, C.[Cheolkon],
Yang, Q.[Qi],
Sun, T.T.[Ting-Ting],
Fu, Q.T.[Qing-Tao],
Song, H.[Hyoseob],
Low light image enhancement with dual-tree complex wavelet transform,
JVCIR(42), No. 1, 2017, pp. 28-36.
Elsevier DOI
1701
Contrast enhancement
BibRef
Su, H.[Haonan],
Yu, L.[Long],
Jung, C.[Cheolkon],
Joint Contrast Enhancement and Noise Reduction of Low Light Images
Via JND Transform,
MultMed(24), 2022, pp. 17-32.
IEEE DOI
2202
Visualization, Noise reduction, Transforms, Image color analysis,
Colored noise, Adaptation models, Lighting, Contrast enhancement,
Weber's law
BibRef
Mei, L.[Lin],
Jung, C.[Cheolkon],
Low Light Image Enhancement by Multispectral Fusion and Convolutional
Neural Networks,
ICPR22(203-209)
IEEE DOI
2212
Training, Smoothing methods, Image color analysis, Noise reduction,
Feature extraction, Pattern recognition, Convolutional neural networks
BibRef
Ji, Z.[Zhe],
Jung, C.[Cheolkon],
Subband Adaptive Enhancement of Low Light Images Using Wavelet-Based
Convolutional Neural Networks,
ICIP21(1669-1673)
IEEE DOI
2201
Visualization, Adaptive systems, Noise reduction, Redundancy,
Discrete wavelet transforms, Convolutional neural networks,
wavelet.
BibRef
Lore, K.G.[Kin Gwn],
Akintayo, A.[Adedotun],
Sarkar, S.[Soumik],
LLNet:
A deep autoencoder approach to natural low-light image enhancement,
PR(61), No. 1, 2017, pp. 650-662.
Elsevier DOI
1705
Image enhancement
BibRef
Lim, J.[Jaemoon],
Heo, M.[Minhyeok],
Lee, C.[Chul],
Kim, C.S.[Chang-Su],
Contrast enhancement of noisy low-light images based on
structure-texture-noise decomposition,
JVCIR(45), No. 1, 2017, pp. 107-121.
Elsevier DOI
1704
Image enhancement
BibRef
Park, J.[Jaemin],
Vien, A.G.[An Gia],
Cha, M.[Minhee],
Pham, T.T.[Thuy Thi],
Kim, H.[Hanul],
Lee, C.[Chul],
Multiple transformation function estimation for image enhancement,
JVCIR(95), 2023, pp. 103863.
Elsevier DOI
2309
Image enhancement, Multiple transformation functions,
Color representation, Histogram representation
BibRef
Park, J.[Jaemin],
Vien, A.G.[An Gia],
Kim, J.H.[Jin-Hwan],
Lee, C.[Chul],
Histogram-Based Transformation Function Estimation for Low-Light
Image Enhancement,
ICIP22(1-5)
IEEE DOI
2211
Image quality, Histograms, Estimation, Feature extraction,
Data mining, Image enhancement, Low-light image enhancement,
histogram equalization
BibRef
Lim, J.[Jaemoon],
Kim, J.H.[Jin-Hwan],
Sim, J.Y.[Jae-Young],
Kim, C.S.[Chang-Su],
Robust contrast enhancement of noisy low-light images:
Denoising-enhancement-completion,
ICIP15(4131-4135)
IEEE DOI
1512
Low-light image enhancement
BibRef
Kim, J.H.[Jin-Hwan],
Jang, W.D.[Won-Dong],
Park, Y.[Yongsup],
Lee, D.H.[Dong-Hahk],
Sim, J.Y.[Jae-Young],
Kim, C.S.[Chang-Su],
Temporally x real-time video dehazing,
ICIP12(969-972).
IEEE DOI
1302
BibRef
Kim, J.H.[Jin-Hwan],
Jang, W.D.[Won-Dong],
Sim, J.Y.[Jae-Young],
Kim, C.S.[Chang-Su],
Optimized contrast enhancement for real-time image and video dehazing,
JVCIR(24), No. 3, April 2013, pp. 410-425.
Elsevier DOI
1303
Image dehazing; Video dehazing; Image restoration; Contrast
enhancement; Temporal coherence; Image enhancement; Optimized dehazing;
Atmospheric light estimation
BibRef
Ko, S.Y.[Seung-Yong],
Yu, S.[Soohwan],
Park, S.[Seonhee],
Moon, B.[Byeongho],
Kang, W.[Wonseok],
Paik, J.[Joonki],
Variational framework for low-light image enhancement using optimal
transmission map and combined and -minimization,
SP:IC(58), No. 1, 2017, pp. 99-110.
Elsevier DOI
1710
Low-light, image, enhancement
BibRef
Anaya, J.[Josue],
Barbu, A.[Adrian],
RENOIR-A dataset for real low-light image noise reduction,
JVCIR(51), 2018, pp. 144-154.
Elsevier DOI
1802
Dataset, Noise Reduction. Image denoising, Denoising dataset, Low light noise,
Poisson-Gaussian noise model
BibRef
Guo, X.,
Li, Y.,
Ling, H.,
LIME: Low-Light Image Enhancement via Illumination Map Estimation,
IP(26), No. 2, February 2017, pp. 982-993.
IEEE DOI
1702
estimation theory
BibRef
Li, C.Y.[Chong-Yi],
Guo, J.C.[Ji-Chang],
Porikli, F.M.[Fatih M.],
Pang, Y.W.[Yan-Wei],
LightenNet:
A Convolutional Neural Network for weakly illuminated image enhancement,
PRL(104), 2018, pp. 15-22.
Elsevier DOI
1804
Low light image enhancement,
Weak illumination image enhancement, Image degradation, CNNs
BibRef
Yu, S.,
Zhu, H.,
Low-Illumination Image Enhancement Algorithm Based on a Physical
Lighting Model,
CirSysVideo(29), No. 1, January 2019, pp. 28-37.
IEEE DOI
1901
Lighting, Attenuation, Image restoration, Image color analysis,
Degradation, Scattering, Atmospheric modeling, Image enhancement,
weighted guide filter
BibRef
Tang, C.Y.[Chao-Ying],
Wang, Y.[Yeru],
Feng, H.J.[Hua-Jun],
Xu, Z.H.[Zhi-Hai],
Li, Q.[Qi],
Chen, Y.T.[Yue-Ting],
Low-light image enhancement with strong light weakening and bright halo
suppressing,
IET-IPR(13), No. 3, February 2019, pp. 537-542.
DOI Link
1903
BibRef
Ren, Y.R.[Yu-Rui],
Ying, Z.Q.[Zhen-Qiang],
Li, T.H.,
Li, G.[Ge],
LECARM: Low-Light Image Enhancement Using the Camera Response Model,
CirSysVideo(29), No. 4, April 2019, pp. 968-981.
IEEE DOI
1904
Cameras, Lighting, Image enhancement, Image color analysis,
Nonlinear distortion, Histograms, Camera response function,
contrast enhancement
BibRef
Ying, Z.Q.[Zhen-Qiang],
Li, G.[Ge],
Ren, Y.R.[Yu-Rui],
Wang, R.G.[Rong-Gang],
Wang, W.M.[Wen-Min],
A New Low-Light Image Enhancement Algorithm Using Camera Response
Model,
CVPV17(3015-3022)
IEEE DOI
1802
BibRef
And:
A New Image Contrast Enhancement Algorithm Using Exposure Fusion
Framework,
CAIP17(II: 36-46).
Springer DOI
1708
Cameras, Distortion, Estimation, Image color analysis,
Image enhancement, Lighting, Mathematical model
BibRef
Loh, Y.P.[Yuen Peng],
Liang, X.F.[Xue-Feng],
Chan, C.S.[Chee Seng],
Low-light image enhancement using Gaussian Process for features
retrieval,
SP:IC(74), 2019, pp. 175-190.
Elsevier DOI
1904
Low-light, Image enhancement, Gaussian Process, Convolutional neural network
BibRef
Ren, W.Q.[Wen-Qi],
Liu, S.F.[Si-Fei],
Ma, L.[Lin],
Xu, Q.Q.[Qian-Qian],
Xu, X.Y.[Xiang-Yu],
Cao, X.C.[Xiao-Chun],
Du, J.P.[Jun-Ping],
Yang, M.H.[Ming-Hsuan],
Low-Light Image Enhancement via a Deep Hybrid Network,
IP(28), No. 9, Sep. 2019, pp. 4364-4375.
IEEE DOI
1908
image enhancement, recurrent neural nets, content stream,
encoder-decoder network, edge stream, edge details, auto-encoder,
recurrent neural network
BibRef
Jiang, Q.P.[Qiu-Ping],
Mao, Y.D.[Yu-Dong],
Cong, R.[Runmin],
Ren, W.Q.[Wen-Qi],
Huang, C.[Chao],
Shao, F.[Feng],
Unsupervised Decomposition and Correction Network for Low-Light Image
Enhancement,
ITS(23), No. 10, October 2022, pp. 19440-19455.
IEEE DOI
2210
Lighting, Training, Image enhancement, Visualization,
Computational modeling, Training data, Task analysis,
Retinex model
BibRef
Yue, G.H.[Guang-Hui],
Gao, J.[Jie],
Cong, R.[Runmin],
Zhou, T.W.[Tian-Wei],
Li, L.[Leida],
Wang, T.F.[Tian-Fu],
Deep Pyramid Network for Low-Light Endoscopic Image Enhancement,
CirSysVideo(34), No. 5, May 2024, pp. 3834-3845.
IEEE DOI
2405
Lighting, Feature extraction, Task analysis, Reflection,
Image enhancement, Reflectivity, Random access memory,
image quality
BibRef
Wang, Y.F.[Yun-Fei],
Liu, H.M.[He-Ming],
Fu, Z.W.[Zhao-Wang],
Low-Light Image Enhancement via the Absorption Light Scattering Model,
IP(28), No. 11, November 2019, pp. 5679-5690.
IEEE DOI
1909
Lighting, Atmospheric modeling, Imaging, Image color analysis,
Mathematical model, Image enhancement, Absorption,
minimal channel
BibRef
Fu, G.,
Duan, L.,
Xiao, C.,
A Hybrid L2 -LP Variational Model For Single Low-Light Image
Enhancement With Bright Channel Prior,
ICIP19(1925-1929)
IEEE DOI
1910
Retinex, reflectance, illumination, alternating minimization
BibRef
Wu, Y.H.[Ya-Hong],
Zheng, J.Y.[Jie-Ying],
Song, W.[Wanru],
Liu, F.[Feng],
Low light image enhancement based on non-uniform illumination prior
model,
IET-IPR(13), No. 13, November 2019, pp. 2448-2456.
DOI Link
1911
BibRef
Wu, Y.H.[Ya-Hong],
Song, W.[Wanru],
Zheng, J.Y.[Jie-Ying],
Liu, F.[Feng],
Non-uniform low-light image enhancement via non-local similarity
decomposition model,
SP:IC(93), 2021, pp. 116141.
Elsevier DOI
2103
Non-uniform low-light image enhancement, Similarity measure,
Non-local similarity decomposition, Edge information,
Reflectance and illumination
BibRef
Liu, X.L.[Xia-Lin],
Sun, Y.W.[Yi-Wei],
Shi, J.H.[Jian-Hong],
Zeng, G.H.[Gui-Hua],
Photon efficiency of computational ghost imaging with single-photon
detection,
JOSA-A(35), No. 10, October 2018, pp. 1741-1748.
DOI Link
1912
Computational imaging, Digital micromirror devices,
Image quality, Imaging systems, Low light level techniques, Low light levels
BibRef
Lee, H.,
Sohn, K.,
Min, D.,
Unsupervised Low-Light Image Enhancement Using Bright Channel Prior,
SPLetters(27), 2020, pp. 251-255.
IEEE DOI
2002
Unsupervised learning, low-light image enhancement, bright channel prior
BibRef
Srinivas, K.[Kankanala],
Bhandari, A.K.[Ashish Kumar],
Low light image enhancement with adaptive sigmoid transfer function,
IET-IPR(14), No. 4, 27 March 2020, pp. 668-678.
DOI Link
2003
BibRef
Hsieh, P.W.[Po-Wen],
Shao, P.C.A.[Pei-Chi-Ang],
Yang, S.Y.[Suh-Yuh],
Adaptive Variational Model for Contrast Enhancement of Low-Light
Images,
SIIMS(13), No. 1, 2020, pp. 1-28.
DOI Link
2004
BibRef
Li, M.D.[Ma-Ding],
Liu, J.Y.[Jia-Ying],
Yang, W.H.[Wen-Han],
Sun, X.Y.[Xiao-Yan],
Guo, Z.M.[Zong-Ming],
Structure-Revealing Low-Light Image Enhancement Via Robust Retinex
Model,
IP(27), No. 6, June 2018, pp. 2828-2841.
IEEE DOI
1804
image enhancement, optimisation,
augmented Lagrange multiplier based alternating
direction minimization algorithm, structure-revealing.
BibRef
Ren, X.,
Yang, W.,
Cheng, W.,
Liu, J.,
LR3M: Robust Low-Light Enhancement via Low-Rank Regularized Retinex
Model,
IP(29), 2020, pp. 5862-5876.
IEEE DOI
2005
Lighting, Robustness, Noise reduction, Histograms, Minimization,
Visualization, Estimation, Low-light enhancement, denoising,
low-rank decomposition
BibRef
Yang, W.H.[Wen-Han],
Yuan, Y.[Ye],
Ren, W.Q.[Wen-Qi],
Liu, J.Y.[Jia-Ying],
Scheirer, W.J.[Walter J.],
Wang, Z.Y.[Zhang-Yang],
Zhang, T.H.[Tai-Heng],
Zhong, Q.Y.[Qiao-Yong],
Xie, D.[Di],
Pu, S.L.[Shi-Liang],
Zheng, Y.Q.[Yu-Qiang],
Qu, Y.Y.[Yan-Yun],
Xie, Y.H.[Yu-Hong],
Chen, L.[Liang],
Li, Z.H.[Zhong-Hao],
Hong, C.[Chen],
Jiang, H.[Hao],
Yang, S.Y.[Si-Yuan],
Liu, Y.[Yan],
Qu, X.C.[Xiao-Chao],
Wan, P.F.[Peng-Fei],
Zheng, S.[Shuai],
Zhong, M.H.[Min-Hui],
Su, T.Y.[Tai-Yi],
He, L.Z.[Ling-Zhi],
Guo, Y.D.[Yan-Dong],
Zhao, Y.[Yao],
Zhu, Z.F.[Zhen-Feng],
Liang, J.X.[Jin-Xiu],
Wang, J.W.[Jing-Wen],
Chen, T.Y.[Tian-Yi],
Quan, Y.H.[Yu-Hui],
Xu, Y.[Yong],
Liu, B.[Bo],
Liu, X.[Xin],
Sun, Q.[Qi],
Lin, T.Y.[Ting-Yu],
Li, X.C.[Xiao-Chuan],
Lu, F.[Feng],
Gu, L.[Lin],
Zhou, S.D.[Sheng-Di],
Cao, C.[Cong],
Zhang, S.F.[Shi-Feng],
Chi, C.[Cheng],
Zhuang, C.B.[Chu-Bing],
Lei, Z.[Zhen],
Li, S.Z.[Stan Z.],
Wang, S.Z.[Shi-Zheng],
Liu, R.Z.[Rui-Zhe],
Yi, D.[Dong],
Zuo, Z.M.[Zhe-Ming],
Chi, J.N.[Jian-Ning],
Wang, H.[Huan],
Wang, K.[Kai],
Liu, Y.X.[Yi-Xiu],
Gao, X.Y.[Xing-Yu],
Chen, Z.Y.[Zhen-Yu],
Guo, C.[Chang],
Li, Y.Z.[Yong-Zhou],
Zhong, H.C.[Hui-Cai],
Huang, J.[Jing],
Guo, H.[Heng],
Yang, J.F.[Jian-Fei],
Liao, W.J.[Wen-Juan],
Yang, J.G.[Jian-Gang],
Zhou, L.G.[Li-Guo],
Feng, M.Y.[Ming-Yue],
Qin, L.K.[Li-Kun],
Advancing Image Understanding in Poor Visibility Environments:
A Collective Benchmark Study,
IP(29), 2020, pp. 5737-5752.
IEEE DOI
2005
Poor visibility environment, object detection, face detection,
haze, rain, low-light conditions
BibRef
Saha, R.[Rappy],
Banik, P.P.[Partha Pratim],
Gupta, S.S.[Shantanu Sen],
Kim, K.D.[Ki-Doo],
Combining highlight removal and low-light image enhancement technique
for HDR-like image generation,
IET-IPR(14), No. 9, 20 July 2020, pp. 1851-1861.
DOI Link
2007
BibRef
Wang, L.,
Liu, Z.,
Siu, W.,
Lun, D.P.K.,
Lightening Network for Low-Light Image Enhancement,
IP(29), 2020, pp. 7984-7996.
IEEE DOI
2007
Feature extraction, Task analysis, Lighting, Image resolution,
Reflectivity, Image enhancement, Data mining,
deep learning
BibRef
Kim, J.W.[Jae-Woo],
Ryu, J.H.[Je-Ho],
Kim, J.O.[Jong-Ok],
Deep gradual flash fusion for low-light enhancement,
JVCIR(72), 2020, pp. 102903.
Elsevier DOI
1806
Image fusion, Flash fusion, Pseudo multi-exposure, Auto-encoder,
GAN, Low light enhancement
BibRef
Xie, J.[Junyi],
Bian, H.[Hao],
Wu, Y.[Yuanhang],
Zhao, Y.[Yu],
Shan, L.[Linmin],
Hao, S.J.[Shi-Jie],
Semantically-guided low-light image enhancement,
PRL(138), 2020, pp. 308-314.
Elsevier DOI
2010
Image enhancement, Low light, Semantic information, Simplified retinex model
BibRef
Hao, S.J.[Shi-Jie],
Han, X.[Xu],
Guo, Y.R.[Yan-Rong],
Xu, X.[Xin],
Wang, M.[Meng],
Low-Light Image Enhancement With Semi-Decoupled Decomposition,
MultMed(22), No. 12, December 2020, pp. 3025-3038.
IEEE DOI
2011
Lighting, Task analysis, Imaging, Image edge detection,
Image enhancement, Visualization, Optimization, Low-light images,
Retinex model
BibRef
Fu, Q.X.[Qing-Xu],
Di, X.G.[Xiao-Guang],
Zhang, Y.[Yu],
Learning an adaptive model for extreme low-light raw image processing,
IET-IPR(14), No. 14, December 2020, pp. 3433-3443.
DOI Link
2012
BibRef
Lamba, M.,
Rachavarapu, K.K.,
Mitra, K.,
Harnessing Multi-View Perspective of Light Fields for Low-Light
Imaging,
IP(30), 2021, pp. 1501-1513.
IEEE DOI
2101
Image restoration, Cameras, Light fields, Noise reduction,
Estimation, ISO, Visualization, Low-light, light field enhancement,
light field dataset
BibRef
Hu, L.S.[Lin-Shu],
Qin, M.J.[Meng-Jiao],
Zhang, F.[Feng],
Du, Z.H.[Zhen-Hong],
Liu, R.Y.[Ren-Yi],
RSCNN: A CNN-Based Method to Enhance Low-Light Remote-Sensing Images,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Yang, W.,
Wang, W.,
Huang, H.,
Wang, S.,
Liu, J.,
Sparse Gradient Regularized Deep Retinex Network for Robust Low-Light
Image Enhancement,
IP(30), 2021, pp. 2072-2086.
IEEE DOI
2101
Lighting, Image restoration, Image enhancement, Image coding,
Noise reduction, Atmospheric modeling, Minimization,
denoising
BibRef
Niu, J.X.[Jin-Xing],
Jiang, Y.J.[Ya-Jie],
Fu, Y.Y.[Ya-Yun],
Special Issue Retraction:
Research on image sharpening algorithm in weak illumination environment,
IET-IPR(17), No. 1, January 2023, pp. 301.
DOI Link
2301
BibRef
And:
IET-IPR(14), No. 15, 15 December 2020, pp. 3635-3638.
DOI Link
2103
BibRef
Yang, W.H.[Wen-Han],
Wang, S.Q.[Shi-Qi],
Fang, Y.M.[Yu-Ming],
Wang, Y.[Yue],
Liu, J.Y.[Jia-Ying],
Band Representation-Based Semi-Supervised Low-Light Image
Enhancement: Bridging the Gap Between Signal Fidelity and Perceptual
Quality,
IP(30), 2021, pp. 3461-3473.
IEEE DOI
2103
BibRef
Earlier:
From Fidelity to Perceptual Quality: A Semi-Supervised Approach for
Low-Light Image Enhancement,
CVPR20(3060-3069)
IEEE DOI
2008
Visualization, Lighting, Neural networks, Image enhancement,
Image color analysis, Degradation, Visual perception, Low light,
perceptual quality.
Lighting,
Estimation, Image restoration, Colored noise
BibRef
Chen, B.L.[Bao-Liang],
Zhu, L.Y.[Ling-Yu],
Zhu, H.W.[Han-Wei],
Yang, W.H.[Wen-Han],
Song, L.Q.[Lin-Qi],
Wang, S.Q.[Shi-Qi],
Gap-Closing Matters: Perceptual Quality Evaluation and Optimization
of Low-Light Image Enhancement,
MultMed(26), 2024, pp. 3430-3443.
IEEE DOI
2402
Databases, Distortion, Image enhancement, Optimization,
Visualization, Lighting, Quality assessment, optimization
BibRef
Zhang, Y.H.[Yong-Hua],
Guo, X.J.[Xiao-Jie],
Ma, J.Y.[Jia-Yi],
Liu, W.[Wei],
Zhang, J.W.[Jia-Wan],
Beyond Brightening Low-light Images,
IJCV(129), No. 4, April 2021, pp. 1013-1037.
Springer DOI
2104
BibRef
Liu, J.Y.[Jia-Ying],
Xu, D.J.[De-Jia],
Yang, W.H.[Wen-Han],
Fan, M.H.[Min-Hao],
Huang, H.F.[Hao-Feng],
Benchmarking Low-Light Image Enhancement and Beyond,
IJCV(129), No. 4, April 2021, pp. 1153-1184.
Springer DOI
2104
BibRef
Huang, H.F.[Hao-Feng],
Yang, W.H.[Wen-Han],
Hu, Y.Y.[Yue-Yu],
Liu, J.Y.[Jia-Ying],
Raw-guided Enhancing Reprocess of Low-light Image via Deep Exposure
Adjustment,
ACCV20(II:118-133).
Springer DOI
2103
BibRef
Wang, J.S.[Jun-Shu],
Yang, Y.[Yue],
Chen, Y.[Yuan],
Han, Y.X.[Yu-Xing],
LighterGAN: An Illumination Enhancement Method for Urban UAV Imagery,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Lv, F.F.[Fei-Fan],
Li, Y.[Yu],
Lu, F.[Feng],
Attention Guided Low-Light Image Enhancement with a Large Scale
Low-Light Simulation Dataset,
IJCV(129), No. 7, July 2021, pp. 2175-2193.
Springer DOI
2106
BibRef
Miller, S.[Sarah],
Zhang, C.[Chen],
Hirakawa, K.[Keigo],
Multi-Resolution Aitchison Geometry Image Denoising for Low-Light
Photography,
IP(30), 2021, pp. 5724-5738.
IEEE DOI
2106
Noise reduction, Wavelet transforms, Lighting, Geometry, Estimation,
Image denoising, Image edge detection, Image denoising, Poisson,
Aitchison geometry
BibRef
Li, M.[Miao],
Zhou, D.M.[Dong-Ming],
Nie, R.C.[Ren-Can],
Xie, S.D.[Shi-Dong],
Liu, Y.Y.[Yan-Yu],
AMBCR: Low-Light Image Enhancement via Attention Guided Multi-Branch
Construction and Retinex Theory,
IET-IPR(15), No. 9, 2021, pp. 2020-2038.
DOI Link
2106
attention networks, low-light image enhancement,
multi-branch construction, Retinex theory
BibRef
Sandoub, G.[Ghada],
Atta, R.[Randa],
Ali, H.A.[Hesham Arafat],
Abdel-Kader, R.F.[Rabab Farouk],
A low-light image enhancement method based on bright channel prior
and maximum colour channel,
IET-IPR(15), No. 8, 2021, pp. 1759-1772.
DOI Link
2106
BibRef
Parihar, A.S.[Anil Singh],
Singh, K.[Kavinder],
Rohilla, H.[Hrithik],
Asnani, G.[Gul],
Fusion-based simultaneous estimation of reflectance and illumination
for low-light image enhancement,
IET-IPR(15), No. 7, 2021, pp. 1410-1423.
DOI Link
2106
BibRef
Li, F.[Fei],
Zheng, J.B.[Jiang-Bin],
Zhang, Y.F.[Yuan-Fang],
Generative Adversarial Network for Low-Light Image Enhancement,
IET-IPR(15), No. 7, 2021, pp. 1542-1552.
DOI Link
2106
BibRef
Yang, J.Y.[Jing-Yu],
Xu, Y.W.[Yu-Wei],
Yue, H.J.[Huan-Jing],
Jiang, Z.Y.[Zhong-Yu],
Li, K.[Kun],
Low-light image enhancement based on Retinex decomposition and
adaptive gamma correction,
IET-IPR(15), No. 5, 2021, pp. 1189-1202.
DOI Link
2106
BibRef
Ma, C.X.[Cheng-Xu],
Li, D.H.[Dai-Hui],
Zeng, S.Y.[Shang-You],
Zhao, J.[Junbo],
Chen, H.Y.[Hong-Yang],
An efficient framework for deep learning-based light-defect image
enhancement,
IET-IPR(15), No. 7, 2021, pp. 1553-1566.
DOI Link
2106
BibRef
Khan, R.[Rizwan],
Yang, Y.[You],
Liu, Q.[Qiong],
Qaisar, Z.H.[Zahid Hussain],
A ghostfree contrast enhancement method for multiview images without
depth information,
JVCIR(78), 2021, pp. 103175.
Elsevier DOI
2107
Multi-view low-light images, Feature matching, Exposure fusion
BibRef
Kong, X.Y.[Xiang-Yu],
Liu, L.[Lei],
Qian, Y.S.[Yun-Sheng],
Low-Light Image Enhancement via Poisson Noise Aware Retinex Model,
SPLetters(28), 2021, pp. 1540-1544.
IEEE DOI
2108
Lighting, Reflectivity, Kernel, Image enhancement, Noise reduction,
Photonics, Standards, Image denoising, low-light image enhancement,
Retinex model
BibRef
Chen, X.Y.[Xin-Yu],
Li, J.J.[Jin-Jiang],
Hua, Z.[Zhen],
Low-light image enhancement based on exponential Retinex variational
model,
IET-IPR(15), No. 12, 2021, pp. 3003-3019.
DOI Link
2109
BibRef
Xu, X.T.[Xin-Tao],
Li, J.J.[Jin-Jiang],
Hua, Z.[Zhen],
Fan, L.W.[Lin-Wei],
Attention-Based Multi-Channel Feature Fusion Enhancement Network to
Process Low-Light Images,
IET-IPR(16), No. 12, 2022, pp. 3374-3393.
DOI Link
2209
BibRef
Huang, Z.X.[Zhi-Xiong],
Li, J.J.[Jin-Jiang],
Hua, Z.[Zhen],
Fan, L.W.[Lin-Wei],
Attention-based dual-color space fusion network for low-light image
enhancement,
SP:IC(119), 2023, pp. 117060.
Elsevier DOI
2310
Low-light image enhancement, Dual-color space,
Adaptive large-kernel attention, Deep learning
BibRef
Yu, N.[Nana],
Li, J.J.[Jin-Jiang],
Hua, Z.[Zhen],
LBP-based progressive feature aggregation network for low-light image
enhancement,
IET-IPR(16), No. 2, 2022, pp. 535-553.
DOI Link
2201
BibRef
Huang, Z.X.[Zhi-Xiong],
Li, J.J.[Jin-Jiang],
Hua, Z.[Zhen],
Underwater image enhancement via LBP-based attention residual network,
IET-IPR(16), No. 1, 2022, pp. 158-175.
DOI Link
2112
BibRef
Li, J.Q.[Jia-Qian],
Li, J.C.[Jun-Cheng],
Fang, F.M.[Fa-Ming],
Li, F.[Fang],
Zhang, G.X.[Gui-Xu],
Luminance-Aware Pyramid Network for Low-Light Image Enhancement,
MultMed(23), 2021, pp. 3153-3165.
IEEE DOI
2109
Feature extraction, Image enhancement, Lighting, Task analysis,
Image color analysis, pyramid structure
BibRef
Feng, X.M.[Xiao-Mei],
Li, J.J.[Jin-Jiang],
Fan, H.[Hui],
Hierarchical guided network for low-light image enhancement,
IET-IPR(15), No. 13, 2021, pp. 3254-3266.
DOI Link
2110
BibRef
Lv, X.Q.[Xiao-Qian],
Sun, Y.J.[Yu-Jing],
Zhang, J.[Jun],
Jiang, F.[Feng],
Zhang, S.P.[Sheng-Ping],
Low-light image enhancement via deep Retinex decomposition and
bilateral learning,
SP:IC(99), 2021, pp. 116466.
Elsevier DOI
2111
Low-light image enhancement, Image decomposition,
Deep neural network, Attention, Illumination adjustment
BibRef
Malik, S.[Sameer],
Soundararajan, R.[Rajiv],
A low light natural image statistical model for joint contrast
enhancement and denoising,
SP:IC(99), 2021, pp. 116433.
Elsevier DOI
2111
Gaussian scale mixture models, Natural scene statistics,
Contrast enhancement, Low light enhancement, Denoising
BibRef
Lu, K.[Kun],
Zhang, L.H.[Li-Hong],
TBEFN:
A Two-Branch Exposure-Fusion Network for Low-Light Image Enhancement,
MultMed(23), 2021, pp. 4093-4105.
IEEE DOI
2112
Lighting, Noise reduction, Image enhancement, Estimation,
Image reconstruction, Image color analysis, Visualization,
transfer function estimation
BibRef
Lim, S.[Seokjae],
Kim, W.J.[Won-Jun],
DSLR: Deep Stacked Laplacian Restorer for Low-Light Image Enhancement,
MultMed(23), 2021, pp. 4272-4284.
IEEE DOI
2112
Laplace equations, Image restoration, Lighting, Image enhancement,
Visualization, Image color analysis, Histograms,
decomposition-based scheme
BibRef
Qiu, Y.S.[Yan-Sheng],
Chen, J.[Jun],
Wang, Z.[Zheng],
Wang, X.[Xiao],
Lin, C.W.[Chia-Wen],
Spatio-Spectral Feature Fusion for Low-Light Image Enhancement,
SPLetters(28), 2021, pp. 2157-2161.
IEEE DOI
2112
Frequency-domain analysis, Convolution, Image enhancement,
Discrete wavelet transforms, Training, Image color analysis,
spatio-spectral fusion
BibRef
Li, J.J.[Jin-Jiang],
Feng, X.M.[Xiao-Mei],
Hua, Z.[Zhen],
Low-Light Image Enhancement via Progressive-Recursive Network,
CirSysVideo(31), No. 11, November 2021, pp. 4227-4240.
IEEE DOI
2112
Image enhancement, Lighting, Training, Feature extraction,
Brightness, Task analysis, Image color analysis,
attention model
BibRef
Kim, W.J.[Won-Jun],
Low-light image enhancement by diffusion pyramid with residuals,
JVCIR(81), 2021, pp. 103364.
Elsevier DOI
2112
Low-light image enhancement, Scene illumination,
Diffusion pyramid with residuals
BibRef
Al Sobbahi, R.[Rayan],
Tekli, J.[Joe],
Low-Light Homomorphic Filtering Network for integrating image
enhancement and classification,
SP:IC(100), 2022, pp. 116527.
Elsevier DOI
2112
Image enhancement, Low-light conditions, Deep learning,
Object classification, Homomorphic filtering
BibRef
Al Sobbahi, R.[Rayan],
Tekli, J.[Joe],
Comparing deep learning models for low-light natural scene image
enhancement and their impact on object detection and classification:
Overview, empirical evaluation, and challenges,
SP:IC(109), 2022, pp. 116848.
Elsevier DOI
2210
BibRef
Earlier:
Low-Light Image Enhancement Using Image-to-Frequency Filter Learning,
CIAP22(II:693-705).
Springer DOI
2205
Image enhancement, Low-light conditions, Deep learning models,
Object detection and classification, Empirical comparison
BibRef
Zhang, Y.[Yu],
Di, X.G.[Xiao-Guang],
Zhang, B.[Bin],
Ji, R.H.[Rui-Hang],
Wang, C.H.[Chun-Hui],
Better Than Reference in Low-Light Image Enhancement: Conditional
Re-Enhancement Network,
IP(31), 2022, pp. 759-772.
IEEE DOI
2201
Image color analysis, Brightness, Colored noise, Image enhancement,
Training, Distortion, Noise reduction, Low-light image,
color correction
BibRef
Zhang, N.[Ning],
Nex, F.[Francesco],
Kerle, N.[Norman],
Vosselman, G.[George],
LISU: Low-light indoor scene understanding with joint learning of
reflectance restoration,
PandRS(183), 2022, pp. 470-481.
Elsevier DOI
2201
BibRef
Earlier:
Towards Learning Low-light Indoor Semantic Segmentation With
Illumination-invariant Features,
ISPRS21(B2-2021: 427-432).
DOI Link
2201
Semantic segmentation, Deep learning, Intrinsic image decomposition, Low-light
BibRef
Ko, S.[Seonggwan],
Park, J.[Jinsun],
Chae, B.[Byungjoo],
Cho, D.[Donghyeon],
Learning Lightweight Low-Light Enhancement Network Using Pseudo
Well-Exposed Images,
SPLetters(29), 2022, pp. 289-293.
IEEE DOI
2202
Training, Feature extraction, Knowledge engineering,
Image enhancement, Lighting, Dynamic range, Computational modeling,
knowledge distillation
BibRef
Huang, H.F.[Hao-Feng],
Yang, W.H.[Wen-Han],
Hu, Y.Y.[Yue-Yu],
Liu, J.Y.[Jia-Ying],
Duan, L.Y.[Ling-Yu],
Towards Low Light Enhancement With RAW Images,
IP(31), 2022, pp. 1391-1405.
IEEE DOI
2202
Benchmark testing, Training, Pipelines, Image processing, Lighting,
Image enhancement, Histograms, Low-light enhancement, benchmark,
factorized enhancement model
BibRef
Chang, M.[Meng],
Feng, H.J.[Hua-Jun],
Xu, Z.H.[Zhi-Hai],
Li, Q.[Qi],
Low-Light Image Restoration With Short- and Long-Exposure Raw Pairs,
MultMed(24), 2022, pp. 702-714.
IEEE DOI
2202
Imaging, Image color analysis, Colored noise, Task analysis,
Pipelines, Noise reduction, Mobile handsets, Deblurring, denoising,
low-light imaging
BibRef
Zhao, Z.J.[Zun-Jin],
Xiong, B.S.[Bang-Shu],
Wang, L.[Lei],
Ou, Q.F.[Qiao-Feng],
Yu, L.[Lei],
Kuang, F.[Fa],
RetinexDIP: A Unified Deep Framework for Low-Light Image Enhancement,
CirSysVideo(32), No. 3, March 2022, pp. 1076-1088.
IEEE DOI
2203
Lighting, Couplings, Electronics packaging, Image enhancement,
Task analysis, Histograms, Cameras, Low-light image enhancement,
zero-reference
BibRef
Lu, B.[Bibo],
Pang, Z.[Zebang],
Gu, Y.[Yanan],
Zheng, Y.[Yanmei],
Channel splitting attention network for low-light image enhancement,
IET-IPR(16), No. 5, 2022, pp. 1403-1414.
DOI Link
2203
BibRef
Lu, Y.C.[Yu-Cheng],
Jung, S.W.[Seung-Won],
Progressive Joint Low-Light Enhancement and Noise Removal for Raw
Images,
IP(31), 2022, pp. 2390-2404.
IEEE DOI
2203
Noise reduction, Image color analysis, Colored noise, Cameras,
Lighting, Estimation, Task analysis, Convolutional neural network,
low-light image enhancement
BibRef
Chen, L.L.[Liang-Liang],
Guo, L.[Lin],
Cheng, D.Q.[De-Qiang],
Kou, Q.Q.[Qi-Qi],
Structure-Preserving and Color-Restoring Up-Sampling for Single
Low-Light Image,
CirSysVideo(32), No. 4, April 2022, pp. 1889-1902.
IEEE DOI
2204
Lighting, Image reconstruction, Image color analysis, Training,
Reflectivity, Learning systems, Task analysis, Low-light,
color-restoring
BibRef
Shen, L.[Liran],
Ma, Z.Y.[Zhi-Yuan],
Er, M.J.[Meng Joo],
Fan, Y.S.[Yun-Sheng],
Yin, Q.B.[Qing-Bo],
Blind Adaptive Structure-Preserving Imaging Enhancement for Low-Light
Condition,
SPLetters(29), 2022, pp. 917-921.
IEEE DOI
2205
Lighting, Reflectivity, Adaptation models, Low-pass filters,
Image enhancement, Computational complexity, Estimation,
retinex model
BibRef
Shi, Y.M.[Yang-Ming],
Wang, B.Q.[Bin-Quan],
Wu, X.[Xiaopo],
Zhu, M.[Ming],
Unsupervised Low-Light Image Enhancement by Extracting Structural
Similarity and Color Consistency,
SPLetters(29), 2022, pp. 997-1001.
IEEE DOI
2205
Image color analysis, Feature extraction, Training, Optimization,
Signal processing algorithms, Brightness, Lighting,
unsupervised learning
BibRef
Yang, S.L.[Shao-Liang],
Zhou, D.M.[Dong-Ming],
Cao, J.[Jinde],
Guo, Y.[Yanbu],
Rethinking Low-Light Enhancement via Transformer-GAN,
SPLetters(29), 2022, pp. 1082-1086.
IEEE DOI
2205
Transformers, Feature extraction, Generators, Training,
Task analysis, Lighting, Image reconstruction, Vision transformer,
low light enhancement
BibRef
Zhao, J.[Junbo],
Chen, H.Y.[Hong-Yang],
Zeng, S.[Shangyou],
Ma, C.X.[Cheng-Xu],
RISSNet: Retain low-light image details and improve the structural
similarity net,
IET-IPR(16), No. 7, 2022, pp. 1793-1806.
DOI Link
2205
BibRef
Lu, Y.X.[Yu-Xu],
Guo, Y.[Yu],
Liu, R.W.[Ryan Wen],
Ren, W.Q.[Wen-Qi],
MTRBNet: Multi-Branch Topology Residual Block-Based Network for
Low-Light Enhancement,
SPLetters(29), 2022, pp. 1127-1131.
IEEE DOI
2205
Topology, Network topology, Convolution, Visualization,
Image enhancement, Brightness, Lighting, Image enhancement,
multi-branch topology
BibRef
Dhara, S.K.[Sobhan Kanti],
Sen, D.[Debashis],
Exposedness-Based Noise-Suppressing Low-Light Image Enhancement,
CirSysVideo(32), No. 6, June 2022, pp. 3438-3451.
IEEE DOI
2206
Lighting, Image enhancement, Estimation, Computational modeling,
Atmospheric modeling, Noise reduction, Light scattering,
noise suppression
BibRef
Wang, W.C.[Wen-Cheng],
Chen, Z.[Zhenxue],
Yuan, X.H.[Xiao-Hui],
Simple low-light image enhancement based on Weber-Fechner law in
logarithmic space,
SP:IC(106), 2022, pp. 116742.
Elsevier DOI
2206
Logarithmic transformation, Low-light image,
Non-uniform illumination, Weber-Fechner law, Color compensation
BibRef
Li, C.Y.[Chong-Yi],
Guo, C.[Chunle],
Loy, C.C.[Chen Change],
Learning to Enhance Low-Light Image via Zero-Reference Deep Curve
Estimation,
PAMI(44), No. 8, August 2022, pp. 4225-4238.
IEEE DOI
2207
Lighting, Estimation, Training, Image enhancement,
Image color analysis, Dynamic range, Task analysis,
zero-reference learning
BibRef
Li, C.Y.[Chong-Yi],
Guo, C.[Chunle],
Han, L.H.[Ling-Hao],
Jiang, J.[Jun],
Cheng, M.M.[Ming-Ming],
Gu, J.W.[Jin-Wei],
Loy, C.C.[Chen Change],
Low-Light Image and Video Enhancement Using Deep Learning: A Survey,
PAMI(44), No. 12, December 2022, pp. 9396-9416.
IEEE DOI
2212
Lighting, Deep learning, Feature extraction, Supervised learning,
Cameras, Training data, Photography, Image and video restoration,
computational photography
BibRef
Guo, C.[Chunle],
Li, C.Y.[Chong-Yi],
Guo, J.C.[Ji-Chang],
Loy, C.C.[Chen Change],
Hou, J.H.[Jun-Hui],
Kwong, S.[Sam],
Cong, R.M.[Run-Min],
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement,
CVPR20(1777-1786)
IEEE DOI
2008
Lighting, Estimation, Dynamic range, Training, Image color analysis,
Task analysis, Image enhancement
BibRef
Huang, C.Y.[Chao-Yan],
Fang, Y.Y.[Ying-Ying],
Wu, T.T.[Ting-Ting],
Zeng, T.Y.[Tie-Yong],
Zeng, Y.H.[Yong-Hua],
Quaternion Screened Poisson Equation for Low-Light Image Enhancement,
SPLetters(29), 2022, pp. 1417-1421.
IEEE DOI
2207
Quaternions, Image color analysis, Color, Mathematical models,
Image enhancement, Task analysis, Poisson equations,
screened Poisson equation
BibRef
Chang, J.[Jie],
Zhu, G.P.[Guo-Pu],
Zhang, H.L.[Hong-Li],
Zhu, L.Y.[Ling-Yu],
Yang, W.H.[Wen-Han],
Chen, B.L.[Bao-Liang],
Lu, F.B.[Fang-Bo],
Wang, S.Q.[Shi-Qi],
Enlightening Low-Light Images With Dynamic Guidance for Context
Enrichment,
CirSysVideo(32), No. 8, August 2022, pp. 5068-5079.
IEEE DOI
2208
Lighting, Image color analysis, Feature extraction,
Image enhancement, Histograms, Image edge detection,
contextual feature
BibRef
Nie, T.[Ting],
Wang, X.F.[Xiao-Feng],
Liu, H.X.[Hong-Xing],
Li, M.X.[Ming-Xuan],
Nong, S.[Shenkai],
Yuan, H.[Hangfei],
Zhao, Y.C.[Yu-Chen],
Huang, L.[Liang],
Enhancement and Noise Suppression of Single Low-Light Grayscale
Images,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Xu, K.[Kai],
Chen, H.A.[Huai-An],
Xu, C.M.[Chun-Mei],
Jin, Y.[Yi],
Zhu, C.G.[Chan-Gan],
Structure-Texture Aware Network for Low-Light Image Enhancement,
CirSysVideo(32), No. 8, August 2022, pp. 4983-4996.
IEEE DOI
2208
Image enhancement, Image color analysis, Image edge detection,
Task analysis, Lighting, Distortion, Visualization, hybrid loss
BibRef
Lin, Y.H.[Yi-Hsien],
Lu, Y.C.[Yi-Chang],
Low-Light Enhancement Using a Plug-and-Play Retinex Model With
Shrinkage Mapping for Illumination Estimation,
IP(31), 2022, pp. 4897-4908.
IEEE DOI
2208
Lighting, Optimization, Image edge detection, Stars,
Learning systems, Linear programming, Image quality,
alternating direction method of multipliers
BibRef
Wang, Y.[Ya'nan],
Jiang, Z.Q.[Zhu-Qing],
Liu, C.[Chang],
Li, K.[Kai],
Men, A.D.[Ai-Dong],
Wang, H.Y.[Hai-Ying],
Chen, X.B.[Xiao-Bo],
Shedding light on images: Multi-level image brightness enhancement
guided by arbitrary references,
PR(131), 2022, pp. 108867.
Elsevier DOI
2208
Low-light image enhancement, Multi-level mapping,
Arbitrary references, Codec network, Decomposition, Concatenation
BibRef
Quan, Y.Z.[Yi-Zhuo],
Fu, D.[Dong],
Chang, Y.[Yuanfei],
Wang, C.B.[Cheng-Bo],
3D Convolutional Neural Network for Low-Light Image Sequence
Enhancement in SLAM,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Rasheed, M.T.[Muhammad Tahir],
Guo, G.Y.[Gui-Yu],
Shi, D.M.[Da-Ming],
Khan, H.[Hufsa],
Cheng, X.C.[Xiao-Chun],
An Empirical Study on Retinex Methods for Low-Light Image Enhancement,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Wang, Y.[Yong],
Li, B.[Bo],
Jiang, L.J.[Li-Jun],
Yang, W.M.[Wen-Ming],
R2Net: Relight the restored low-light image based on complementarity
of illumination and reflection,
SP:IC(108), 2022, pp. 116800.
Elsevier DOI
2209
Low-light image enhancement, Retinex-based method,
Attention module, Image restoration
BibRef
Wei, K.X.[Kai-Xuan],
Fu, Y.[Ying],
Zheng, Y.Q.[Yin-Qiang],
Yang, J.L.[Jiao-Long],
Physics-Based Noise Modeling for Extreme Low-Light Photography,
PAMI(44), No. 11, November 2022, pp. 8520-8537.
IEEE DOI
2210
Imaging, Noise reduction, Computational modeling, Photonics,
Data models, Training data, Extreme low-light imaging,
low-light denoising dataset
BibRef
Wei, K.X.[Kai-Xuan],
Fu, Y.[Ying],
Yang, J.L.[Jiao-Long],
Huang, H.,
A Physics-Based Noise Formation Model for Extreme Low-Light Raw
Denoising,
CVPR20(2755-2764)
IEEE DOI
2008
Data models, Photonics, Semiconductor device modeling, Cameras,
Noise measurement, Pipelines
BibRef
Liu, X.K.[Xiao-Kai],
Ma, W.H.[Wei-Hao],
Ma, X.R.[Xiao-Rui],
Wang, J.[Jie],
LAE-Net: A locally-adaptive embedding network for low-light image
enhancement,
PR(133), 2023, pp. 109039.
Elsevier DOI
2210
Locally-adaptive, Image enhancement, Multi-distribution,
Image entropy, Kernel selection
BibRef
Liang, J.X.[Jin-Xiu],
Xu, Y.[Yong],
Quan, Y.H.[Yu-Hui],
Shi, B.X.[Bo-Xin],
Ji, H.[Hui],
Self-Supervised Low-Light Image Enhancement Using Discrepant
Untrained Network Priors,
CirSysVideo(32), No. 11, November 2022, pp. 7332-7345.
IEEE DOI
2211
Lighting, Reflectivity, Artificial neural networks, Training data,
Training, Noise reduction, Visualization,
untrained network priors
BibRef
Fan, G.D.[Guo-Dong],
Fan, B.[Bi],
Gan, M.[Min],
Chen, G.Y.[Guang-Yong],
Chen, C.L.P.[C. L. Philip],
Multiscale Low-Light Image Enhancement Network With Illumination
Constraint,
CirSysVideo(32), No. 11, November 2022, pp. 7403-7417.
IEEE DOI
2211
Lighting, Image enhancement, Image color analysis, Deep learning,
Task analysis, Atmospheric modeling, Histograms, Res2Net
BibRef
Liu, C.X.[Chun-Xiao],
Wu, F.D.[Fan-Ding],
Wang, X.[Xun],
EFINet: Restoration for Low-Light Images via Enhancement-Fusion
Iterative Network,
CirSysVideo(32), No. 12, December 2022, pp. 8486-8499.
IEEE DOI
2212
Lighting, Image color analysis, Training, Image enhancement,
Iterative methods, Feature extraction, Task analysis,
light-weight CNNs
BibRef
Peng, B.[Bo],
Zhang, X.Y.[Xuan-Yu],
Lei, J.J.[Jian-Jun],
Zhang, Z.[Zhe],
Ling, N.[Nam],
Huang, Q.M.[Qing-Ming],
LVE-S2D: Low-Light Video Enhancement From Static to Dynamic,
CirSysVideo(32), No. 12, December 2022, pp. 8342-8352.
IEEE DOI
2212
Image enhancement, Video sequences, Training, Task analysis,
Histograms, Correlation, Lighting, Low-light video enhancement, deep learning
BibRef
Guo, X.J.[Xiao-Jie],
Hu, Q.M.[Qi-Ming],
Low-light Image Enhancement via Breaking Down the Darkness,
IJCV(131), No. 1, January 2023, pp. 48-66.
Springer DOI
2301
BibRef
Cotogni, M.[Marco],
Cusano, C.[Claudio],
TreEnhance: A tree search method for low-light image enhancement,
PR(136), 2023, pp. 109249.
Elsevier DOI
2301
Low-light image enhancement, Deep reinforcement learning,
Automatic image retouching, Image processing, Tree search
BibRef
Xu, W.[Wanyan],
Dong, X.[Xingbo],
Ma, L.[Lan],
Teoh, A.B.J.[Andrew Beng Jin],
Lin, Z.X.[Zhi-Xian],
RawFormer: An Efficient Vision Transformer for Low-Light RAW Image
Enhancement,
SPLetters(29), 2022, pp. 2677-2681.
IEEE DOI
2301
Transformers, Convolution, Image enhancement, Image restoration,
Task analysis, Computational modeling, Computational efficiency,
RAW camera data processing
BibRef
Liu, M.[Maomei],
Tang, L.[Lei],
Zhong, S.[Sheng],
Luo, H.Z.[Hang-Zai],
Peng, J.Y.[Jin-Ye],
Learning to recover lost details from the dark,
PRL(165), 2023, pp. 107-113.
Elsevier DOI
2301
Low-light image enhancement, Convolutional neural network, Low-light dataset
BibRef
Cai, R.T.[Rong-Tai],
Chen, Z.K.[Ze-Kun],
Brain-like retinex: A biologically plausible retinex algorithm for
low light image enhancement,
PR(136), 2023, pp. 109195.
Elsevier DOI
2301
Retinex, Low light image enhancement, Contour detection,
Edge detection, Brain-inspired computation, Color constancy, Retinal circuit
BibRef
Hai, J.[Jiang],
Xuan, Z.[Zhu],
Yang, R.[Ren],
Hao, Y.T.[Yu-Tong],
Zou, F.Z.[Feng-Zhu],
Lin, F.[Fang],
Han, S.C.[Song-Chen],
R2RNet: Low-light image enhancement via Real-low to Real-normal
Network,
JVCIR(90), 2023, pp. 103712.
Elsevier DOI
2301
Retinex theory, Low-light image enhancement, Image processing,
Real-world low/normal-light image pairs
BibRef
Hai, J.[Jiang],
Hao, Y.T.[Yu-Tong],
Zou, F.Z.[Feng-Zhu],
Lin, F.[Fang],
Han, S.C.[Song-Chen],
Advanced RetinexNet: A fully convolutional network for low-light
image enhancement,
SP:IC(112), 2023, pp. 116916.
Elsevier DOI
2302
Retinex, Low-light image enhancement, Image processing,
Fully convolutional network
BibRef
Yang, J.[Jie],
Wang, J.[Jun],
Dong, L.L.[Lin-Lu],
Chen, S.Y.[Shu-Yuan],
Wu, H.[Hao],
Zhong, Y.W.[Ya-Wen],
Optimization algorithm for low-light image enhancement based on
Retinex theory,
IET-IPR(17), No. 2, 2023, pp. 505-517.
DOI Link
2302
fast and robust fuzzy C-means, guided filtering,
image enhancement, low-light image
BibRef
Malik, S.[Sameer],
Soundararajan, R.[Rajiv],
Semi-Supervised Learning for Low-light Image Restoration through
Quality Assisted Pseudo-Labeling,
WACV23(4094-4103)
IEEE DOI
2302
Training, Image quality, Training data, Lighting,
Self-supervised learning, Semisupervised learning, Distortion.
BibRef
Zhang, W.[Wei],
Jia, Z.H.[Zhen-Hong],
Yang, J.[Jie],
Kasabov, N.K.[Nikola K.],
A dual channel decomposition and remapping fusion model for low
illumination images with a wide field of view,
SP:IC(113), 2023, pp. 116925.
Elsevier DOI
2303
Wide field of view and low illumination, Image decomposition,
Brightness mapping, Noise suppression
BibRef
Zhang, Z.H.[Zhi-Hong],
Cheng, Y.X.[Yu-Xiao],
Suo, J.L.[Jin-Li],
Bian, L.[Liheng],
Dai, Q.H.[Qiong-Hai],
INFWIDE: Image and Feature Space Wiener Deconvolution Network for
Non-Blind Image Deblurring in Low-Light Conditions,
IP(32), 2023, pp. 1390-1402.
IEEE DOI
2303
Image restoration, Deconvolution, Kernel, Training, Photography,
Convergence, Photonics, Non-blind deblurring, low-light,
deep wiener deconvolution
BibRef
Singh, K.[Kavinder],
Parihar, A.S.[Anil Singh],
DSE-Net: Deep simultaneous estimation network for low-light image
enhancement,
JVCIR(91), 2023, pp. 103780.
Elsevier DOI
2303
Deep learning-based network, Simultaneous estimation,
Illumination, Reflectance, Convolutional neural networks
BibRef
Wang, Y.N.[Yong-Nian],
Zhang, Z.B.[Zhi-Bin],
Global attention retinex network for low light image enhancement,
JVCIR(92), 2023, pp. 103795.
Elsevier DOI
2303
Low light image enhancement, Retinex, Global attention, Channel attention
BibRef
Trung, N.T.[Nguyen Tu],
Le, X.H.[Xuan-Hien],
Tuan, T.M.[Tran Manh],
Enhancing Contrast of Dark Satellite Images Based on Fuzzy
Semi-Supervised Clustering and an Enhancement Operator,
RS(15), No. 6, 2023, pp. 1645.
DOI Link
2304
BibRef
Fan, J.Y.[Jun-Yu],
Li, J.J.[Jin-Jiang],
Hua, Z.[Zhen],
Fan, L.W.[Lin-Wei],
Joint transformer progressive self-calibration network for low light
enhancement,
IET-IPR(17), No. 5, 2023, pp. 1493-1509.
DOI Link
2304
attention mechanism, LBP texture feature,
low-light enhancement, self-calibration, transformer
BibRef
Shi, B.Q.[Bao-Qiang],
Jia, Z.H.[Zhen-Hong],
Yang, J.[Jie],
Kasabov, N.K.[Nikola K.],
Unsupervised Change Detection in Wide-Field Video Images Under Low
Illumination,
CirSysVideo(33), No. 4, April 2023, pp. 1564-1576.
IEEE DOI
2304
Lighting, Surveillance, Clustering algorithms, Speckle,
Remote sensing, Transforms, Wide field of view, difference image
BibRef
Liu, R.S.[Ri-Sheng],
Ma, L.[Long],
Ma, T.Y.[Teng-Yu],
Fan, X.[Xin],
Luo, Z.X.[Zhong-Xuan],
Learning With Nested Scene Modeling and Cooperative Architecture
Search for Low-Light Vision,
PAMI(45), No. 5, May 2023, pp. 5953-5969.
IEEE DOI
2304
Task analysis, Computer architecture, Training, Visualization,
Deep learning, Noise reduction, Image enhancement,
cooperative architecture search
BibRef
Zhou, C.[Chu],
Teng, M.G.[Ming-Gui],
Han, J.[Jin],
Liang, J.X.[Jin-Xiu],
Xu, C.[Chao],
Cao, G.[Gang],
Shi, B.X.[Bo-Xin],
Deblurring Low-Light Images with Events,
IJCV(131), No. 5, May 2023, pp. 1284-1298.
Springer DOI
2305
BibRef
Earlier: A1, A2, A3, A5, A7, Only:
DeLiEve-Net:
Deblurring Low-light Images with Light Streaks and Local Events,
PBDL21(1155-1164)
IEEE DOI
2112
Neural networks, Dynamic range,
Cameras, Spatial resolution, Low latency communication
BibRef
Zhang, K.B.[Kai-Bing],
Yuan, C.[Cheng],
Li, J.[Jie],
Gao, X.B.[Xin-Bo],
Li, M.Q.[Min-Qi],
Multi-Branch and Progressive Network for Low-Light Image Enhancement,
IP(32), 2023, pp. 2295-2308.
IEEE DOI
2305
Image enhancement, Lighting, Degradation, Image color analysis,
Network architecture, Technological innovation, Task analysis,
recurrent network
BibRef
Wang, M.L.[Man-Li],
Li, J.Y.[Jia-Yue],
Zhang, C.S.[Chang-Sen],
Low-Light Image Enhancement by Deep Learning Network for Improved
Illumination Map,
CVIU(232), 2023, pp. 103681.
Elsevier DOI
2305
Low-light image enhancement, Retinex theory,
Convolutional neural networks, Depth-separable convolution, Illumination map
BibRef
He, L.[Lei],
Liu, S.X.[Shou-Xin],
Long, W.[Wei],
Li, Y.Y.[Yan-Yan],
Low-light image enhancement via span correction function and discrete
mapping model,
IET-IPR(17), No. 6, 2023, pp. 1812-1836.
DOI Link
2305
brightness enhancement, contrast enhancement, discrete mapping,
grey span characterization, low-light image
BibRef
Lu, H.X.[Hao-Xiang],
Liu, Z.B.[Zhen-Bing],
Lan, R.[Rushi],
Pan, X.P.[Xi-Peng],
Gong, J.M.[Jun-Ming],
Retinex-inspired contrast stretch and detail boosting for lowlight
image enhancement,
IET-IPR(17), No. 6, 2023, pp. 1718-1738.
DOI Link
2305
image enhancement, image fusion, image processing
BibRef
Zhou, F.[Fei],
Sun, X.[Xin],
Dong, J.Y.[Jun-Yu],
Zhu, X.X.[Xiao Xiang],
SurroundNet: Towards effective low-light image enhancement,
PR(141), 2023, pp. 109602.
Elsevier DOI
2306
Image processing, Image enhancement,
Convolution Neural Network, Surround function, Lightweight
BibRef
Lim, C.C.[Choon Chen],
Loh, Y.P.[Yuen Peng],
Wong, L.K.[Lai-Kuan],
LAU-Net: A low light image enhancer with attention and resizing
mechanisms,
SP:IC(115), 2023, pp. 116971.
Elsevier DOI
2306
Low-light image enhancement, Advanced U-Net, Attention, Resizing modules
BibRef
Li, P.Y.[Peng-Yue],
Chen, X.[Xi'ai],
Tian, J.[Jiandong],
Tang, Y.D.[Yan-Dong],
Progressive feature-aware recurrent net for low-light image
enhancement,
SP:IC(115), 2023, pp. 116966.
Elsevier DOI
2306
Low light enhancement, Progressive recurrent network,
Coordinated attention, Cumulative learning
BibRef
Zhang, X.[Xin],
Wang, X.[Xia],
Yan, C.D.[Chang-Da],
LL-CSFormer: A Novel Image Denoiser for Intensified CMOS Sensing
Images under a Low Light Environment,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link
2306
BibRef
Park, J.M.[Jae-Min],
Hong, S.[Sungchul],
Shin, H.S.[Hyu-Soung],
Pilot Study of Low-Light Enhanced Terrain Mapping for Robotic
Exploration in Lunar PSRs,
RS(15), No. 13, 2023, pp. 3412.
DOI Link
2307
BibRef
Zhang, X.[Xupei],
Qin, H.L.[Han-Lin],
Yu, Y.[Yue],
Yan, X.[Xiang],
Yang, S.L.[Shang-Lin],
Wang, G.[Guanghao],
Unsupervised Low-Light Image Enhancement via Virtual Diffraction
Information in Frequency Domain,
RS(15), No. 14, 2023, pp. 3580.
DOI Link
2307
BibRef
Simoneau, A.[Alexandre],
Aubé, M.[Martin],
Methods to Calibrate a Digital Colour Camera as a Multispectral
Imaging Sensor in Low Light Conditions,
RS(15), No. 14, 2023, pp. 3634.
DOI Link
2307
BibRef
Zhang, S.S.[Shan-Si],
Meng, N.[Nan],
Lam, E.Y.[Edmund Y.],
LRT: An Efficient Low-Light Restoration Transformer for Dark Light
Field Images,
IP(32), 2023, pp. 4314-4326.
IEEE DOI
2308
Transformers, Image restoration, Lighting, Task analysis,
Noise reduction, Head, Feature extraction, Light field,
noise parameters
BibRef
Jiang, N.F.[Nan-Feng],
Lin, J.H.[Jun-Hong],
Zhang, T.[Ting],
Zheng, H.F.[Hai-Feng],
Zhao, T.S.[Tie-Song],
Low-Light Image Enhancement via Stage-Transformer-Guided Network,
CirSysVideo(33), No. 8, August 2023, pp. 3701-3712.
IEEE DOI
2308
Degradation, Transformers, Task analysis, Lighting, Training,
Feature extraction, Visualization, Low-light image enhancement,
degradation query
BibRef
Kandula, P.[Praveen],
Suin, M.[Maitreya],
Rajagopalan, A.N.,
Illumination-Adaptive Unpaired Low-Light Enhancement,
CirSysVideo(33), No. 8, August 2023, pp. 3726-3736.
IEEE DOI
2308
Lighting, Task analysis, Cameras, Roads, Image restoration,
Image enhancement, Histograms, Unsupervised learning,
context-guided illumination-adaptive norm
BibRef
Zhang, Z.[Zenan],
Guo, J.[Jichang],
Yue, H.H.[Hui-Hui],
Wang, Y.D.[Yu-Dong],
Global guidance-based integration network for salient object
detection in low-light images,
JVCIR(95), 2023, pp. 103862.
Elsevier DOI
2309
Low-light images, Salient object detection,
Global information flow,
U-shaped attention refinement
BibRef
Jin, H.Y.[Hai-Yan],
Wang, Q.[Qiaobin],
Su, H.[Haonan],
Xiao, Z.L.[Zhao-Lin],
Event-guided low light image enhancement via a dual branch GAN,
JVCIR(95), 2023, pp. 103887.
Elsevier DOI
2309
Low-light enhancement, Feature fusion, Event camera, Gradient reconstruction
BibRef
Lv, X.Q.[Xiao-Qian],
Zhang, S.P.[Sheng-Ping],
Wang, C.Y.[Chen-Yang],
Zhang, W.G.[Wei-Gang],
Yao, H.X.[Hong-Xun],
Huang, Q.M.[Qing-Ming],
Unsupervised Low-Light Video Enhancement With Spatial-Temporal
Co-Attention Transformer,
IP(32), 2023, pp. 4701-4715.
IEEE DOI
2309
BibRef
Huang, J.[Jie],
Fu, X.Y.[Xue-Yang],
Xiao, Z.[Zeyu],
Zhao, F.[Feng],
Xiong, Z.W.[Zhi-Wei],
Low-Light Stereo Image Enhancement,
MultMed(25), 2023, pp. 2978-2992.
IEEE DOI
2309
BibRef
Tang, H.P.[Hua-Peng],
Qin, D.Y.[Dan-Yang],
Yang, J.Q.[Jia-Qiang],
Bie, H.[Haoze],
Yan, M.[Mengying],
Zhang, G.X.[Geng-Xin],
Ma, L.[Lin],
Target Localization Method Based on Image Degradation Suppression and
Multi-Similarity Fusion in Low-Illumination Environments,
IJGI(12), No. 8, 2023, pp. 300.
DOI Link
2309
BibRef
Yang, B.[Biao],
Zheng, L.L.[Liang-Liang],
Wu, X.B.[Xia-Bin],
Gao, T.[Tan],
Chen, X.L.[Xiao-Long],
Low-Illumination Image Enhancement Using Local Gradient Relative
Deviation for Retinex Models,
RS(15), No. 17, 2023, pp. 4327.
DOI Link
2310
BibRef
Ma, L.[Long],
Liu, R.S.[Ri-Sheng],
Wang, Y.Y.[Yi-Yang],
Fan, X.[Xin],
Luo, Z.X.[Zhong-Xuan],
Low-Light Image Enhancement via Self-Reinforced Retinex Projection
Model,
MultMed(25), 2023, pp. 3573-3586.
IEEE DOI
2310
BibRef
Lei, X.Z.[Xiao-Zhou],
Fei, Z.X.[Zi-Xiang],
Zhou, W.J.[Wen-Ju],
Zhou, H.Y.[Hui-Yu],
Fei, M.[Minrui],
Low-Light Image Enhancement Using the Cell Vibration Model,
MultMed(25), 2023, pp. 4439-4454.
IEEE DOI
2310
BibRef
Lei, X.Z.[Xiao-Zhou],
Fei, Z.X.[Zi-Xiang],
Zhou, W.J.[Wen-Ju],
Zhou, H.Y.[Hui-Yu],
Fei, M.[Minrui],
Low-light image enhancement based on cell vibration energy model and
lightness difference,
CVIU(247), 2024, pp. 104079.
Elsevier DOI Code:
WWW Link.
2408
Low light, Image enhancement, Cell vibration model, HSV space, Weibull distribution
BibRef
Han, G.[Guang],
Wang, Y.F.[Ying-Fan],
Liu, J.X.[Ji-Xin],
Zeng, F.[Fanyu],
Low-light images enhancement and denoising network based on
unsupervised learning multi-stream feature modeling,
JVCIR(96), 2023, pp. 103932.
Elsevier DOI
2310
Low-light enhancement, Generative adversarial network,
Multi-stream modeling, Multi-scale feature fusion
BibRef
Wang, W.C.[Wen-Cheng],
Yan, D.L.[Dong-Liang],
Wu, X.J.[Xiao-Jin],
He, W.[Weikai],
Chen, Z.[Zhenxue],
Yuan, X.H.[Xiao-Hui],
Li, L.[Lun],
Low-light image enhancement based on virtual exposure,
SP:IC(118), 2023, pp. 117016.
Elsevier DOI
2310
Low-light image enhancement, Virtual exposure, Image fusion,
Gamma correction, Camera response function
BibRef
Ma, Q.T.[Qian-Ting],
Wang, Y.[Yang],
Zeng, T.Y.[Tie-Yong],
Retinex-Based Variational Framework for Low-Light Image Enhancement
and Denoising,
MultMed(25), 2023, pp. 5580-5588.
IEEE DOI
2311
BibRef
Zhao, Z.J.[Zun-Jin],
Lin, H.X.[He-Xiu],
Shi, D.M.[Da-Ming],
Zhou, G.Q.[Guo-Qing],
A non-regularization self-supervised Retinex approach to low-light
image enhancement with parameterized illumination estimation,
PR(146), 2024, pp. 110025.
Elsevier DOI Code:
WWW Link.
2311
Low-light image enhancement, Illumination estimation,
Parameterization, Bilateral grid, Non-regularization
BibRef
Jeon, J.J.[Jong Ju],
Park, J.Y.[Jun Young],
Eom, I.K.[Il Kyu],
Low-light image enhancement using gamma correction prior in mixed
color spaces,
PR(146), 2024, pp. 110001.
Elsevier DOI Code:
WWW Link.
2311
Low-light image enhancement, Gamma correction prior, Mixed color spaces,
Transmission map, Inverted image, Atmospheric scattering model
BibRef
Xu, J.Z.[Jing-Zhao],
Yuan, M.[Mengke],
Yan, D.M.[Dong-Ming],
Wu, T.[Tieru],
Illumination Guided Attentive Wavelet Network for Low-Light Image
Enhancement,
MultMed(25), 2023, pp. 6258-6271.
IEEE DOI
2311
BibRef
Tang, H.[Huapeng],
Qin, D.Y.[Dan-Yang],
Yang, J.Q.[Jia-Qiang],
Bie, H.[Haoze],
Li, Y.[Yue],
Zhu, Y.[Yong],
Ma, L.[Lin],
Target Search for Joint Local and High-Level Semantic Information
Based on Image Preprocessing Enhancement in Indoor Low-Light
Environments,
IJGI(12), No. 10, 2023, pp. 400.
DOI Link
2311
BibRef
Lin, S.D.[Shi-Deng],
Tang, F.[Fan],
Dong, W.M.[Wei-Ming],
Pan, X.J.[Xing-Jia],
Xu, C.S.[Chang-Sheng],
SMNet: Synchronous Multi-Scale Low Light Enhancement Network With
Local and Global Concern,
MultMed(25), 2023, pp. 9506-9517.
IEEE DOI
2312
BibRef
Feng, H.[Hansen],
Wang, L.Z.[Li-Zhi],
Wang, Y.Z.[Yu-Zhi],
Fan, H.Q.[Hao-Qiang],
Huang, H.[Hua],
Learnability Enhancement for Low-Light Raw Image Denoising:
A Data Perspective,
PAMI(46), No. 1, January 2024, pp. 370-387.
IEEE DOI
2312
BibRef
Hu, X.[Xin],
Wang, J.H.[Jin-Hua],
Xu, S.[Sunhan],
Lightweight and Fast Low-Light Image Enhancement Method Based on
PoolFormer,
IEICE(E107-D), No. 1, January 2024, pp. 157-160.
WWW Link.
2401
BibRef
Luo, Y.[Yu],
You, B.[Bijia],
Yue, G.H.[Guang-Hui],
Ling, J.[Jie],
Pseudo-Supervised Low-Light Image Enhancement With Mutual Learning,
CirSysVideo(34), No. 1, January 2024, pp. 85-96.
IEEE DOI
2401
BibRef
Shi, Y.Y.[Yuan-Yuan],
Fu, X.L.[Xiao-Long],
Li, Y.[Yunan],
Miao, K.B.[Kai-Bin],
Liu, X.Z.[Xiang-Zeng],
Zhao, B.C.[Bo-Cheng],
Miao, Q.G.[Qi-Guang],
A Semi-Supervised Underexposed Image Enhancement Network With
Supervised Context Attention and Multi-Exposure Fusion,
MultMed(26), 2024, pp. 1229-1243.
IEEE DOI
2402
Training, Visualization, Image color analysis, Fuses,
Image edge detection, Lighting, Generative adversarial networks,
supervised context attention
BibRef
Wang, X.Z.[Xing-Zheng],
Chen, K.Q.[Kai-Qiang],
Wang, Z.X.[Zi-Xuan],
Huang, W.H.[Wen-Hao],
PMSNet: Parallel Multi-Scale Network for Accurate Low-Light
Light-Field Image Enhancement,
MultMed(26), 2024, pp. 2041-2055.
IEEE DOI
2402
Correlation, Feature extraction, Convolution, Spatial resolution,
Image reconstruction, Lighting, Low-light light field,
3D convolution
BibRef
Jiang, Y.[Yu],
Wang, Y.[Yuehang],
Li, S.Q.[Si-Qi],
Zhang, Y.J.[Yong-Ji],
Zhao, M.H.[Ming-Hao],
Gao, Y.[Yue],
Event-Based Low-Illumination Image Enhancement,
MultMed(26), 2024, pp. 1920-1931.
IEEE DOI
2402
Image reconstruction, Streaming media, Cameras, Feature extraction,
Image enhancement, Image color analysis, Visualization,
transformer
BibRef
Wu, K.[Kangle],
Huang, J.[Jun],
Ma, Y.[Yong],
Fan, F.[Fan],
Ma, J.Y.[Jia-Yi],
Cycle-Retinex: Unpaired Low-Light Image Enhancement via
Retinex-Inline CycleGAN,
MultMed(26), 2024, pp. 1213-1228.
IEEE DOI
2402
Image enhancement, Image color analysis, Image restoration, Lighting,
Colored noise, Degradation, Deep learning, unsupervised learning
BibRef
Xu, H.[Han],
Zhang, H.[Hao],
Yi, X.P.[Xun-Peng],
Ma, J.Y.[Jia-Yi],
CRetinex: A Progressive Color-Shift Aware Retinex Model for Low-Light
Image Enhancement,
IJCV(132), No. 1, January 2024, pp. 3610-3632.
Springer DOI
2409
BibRef
Zhou, M.L.[Ming-Liang],
Wu, X.T.[Xing-Tai],
Wei, X.[Xuekai],
Xiang, T.[Tao],
Fang, B.[Bin],
Kwong, S.[Sam],
Low-Light Enhancement Method Based on a Retinex Model for Structure
Preservation,
MultMed(26), 2024, pp. 650-662.
IEEE DOI
2402
Lighting, Reflectivity, Image enhancement, Dispersion, Standards, Sensitivity,
Histograms, Coefficient of variation, retinex model, structure-preserving
BibRef
Lin, C.Y.[Chun-Yi],
Haq, M.A.[Muhamad Amirul],
Chen, J.H.[Jiun-Han],
Ruan, S.J.[Shanq-Jang],
Naroska, E.[Edwin],
Efficient Saliency Map Detection for Low-Light Images Based on Image
Gradient,
CirSysVideo(34), No. 2, February 2024, pp. 852-865.
IEEE DOI
2402
Image enhancement, Deep learning, Object detection,
Neural networks, Lighting, Histograms, Saliency detection,
saliency map detection
BibRef
Ye, D.J.[Dong-Jie],
Ni, Z.K.[Zhang-Kai],
Yang, W.H.[Wen-Han],
Wang, H.[Hanli],
Wang, S.Q.[Shi-Qi],
Kwong, S.[Sam],
Glow in the Dark: Low-Light Image Enhancement With External Memory,
MultMed(26), 2024, pp. 2148-2163.
IEEE DOI
2402
Testing, Image enhancement, Transformers, Training data, Training,
Histograms, Lighting, Low-light image enhancement, memory module,
vision transformer
BibRef
Li, X.S.[Xiang-Sheng],
Liu, M.[Manlu],
Ling, Q.[Qiang],
Pixel-Wise Gamma Correction Mapping for Low-Light Image Enhancement,
CirSysVideo(34), No. 2, February 2024, pp. 681-694.
IEEE DOI
2402
Lighting, Visualization, Image enhancement, Deep learning,
Unsupervised learning, Computational modeling, Task analysis
BibRef
Ni, D.D.[Dong-Dong],
Jia, Z.H.[Zhen-Hong],
Yang, J.[Jie],
Kasabov, N.K.[Nikola K.],
Online Low-Light Sand-Dust Video Enhancement Using Adaptive Dynamic
Brightness Correction and a Rolling Guidance Filter,
MultMed(26), 2024, pp. 2192-2206.
IEEE DOI
2402
Streaming media, Brightness, Image color analysis,
Heuristic algorithms, Image enhancement, Lighting, Navigation,
dual-threshold interframe detection strategy
BibRef
Singh, K.[Kavinder],
Parihar, A.S.[Anil Singh],
MRN-LOD: Multi-exposure Refinement Network for Low-light Object
Detection,
JVCIR(99), 2024, pp. 104079.
Elsevier DOI
2403
Object detection, Multi-exposure images,
Adaptive refinement network, Low-light images, Feature extraction
BibRef
Ye, J.[Jing],
Qiu, C.Z.[Chang-Zhen],
Zhang, Z.Y.[Zhi-Yong],
SNR-Prior Guided Trajectory-Aware Transformer for Low-Light Video
Enhancement,
CirSysVideo(34), No. 3, March 2024, pp. 1873-1885.
IEEE DOI
2403
Transformers, Signal to noise ratio, Lighting,
Image reconstruction, Image enhancement, Video sequences, deep learning
BibRef
Wang, Z.[Zhen],
Zhang, X.H.[Xiao-Huan],
Contextual recovery network for low-light image enhancement with
texture recovery,
JVCIR(99), 2024, pp. 104050.
Elsevier DOI
2403
Low light enhancement, Texture optimization,
Squeeze-excitation, Information aggregation
BibRef
Xie, D.[Dian],
Xing, H.J.[Hua-Jun],
Chen, L.[Liangyu],
Hao, S.J.[Shi-Jie],
A lightness-aware loss for low-light image enhancement,
PRL(179), 2024, pp. 123-129.
Elsevier DOI
2403
Low-light image enhancement, Illumination distribution, Loss function
BibRef
Li, X.F.[Xiao-Fang],
Wang, W.W.[Wei-Wei],
Feng, X.C.[Xiang-Chu],
Li, M.[Min],
Deep Parametric Retinex Decomposition Model for Low-Light Image
Enhancement,
CVIU(241), 2024, pp. 103948.
Elsevier DOI
2403
Low-light image enhancement, Parametric Retinex decomposition,
Deep network, Denoising
BibRef
Dang, J.C.[Jia-Chen],
Zhong, Y.[Yong],
Qin, X.L.[Xiao-Lin],
PPformer: Using pixel-wise and patch-wise cross-attention for
low-light image enhancement,
CVIU(241), 2024, pp. 103930.
Elsevier DOI
2403
Low-light image enhancement, Cross-attention, Lightweight,
CNN-transformer hybrid network
BibRef
Jiang, H.[Hai],
Ren, Y.[Yang],
Han, S.C.[Song-Chen],
Revisiting coarse-to-fine strategy for low-light image enhancement
with deep decomposition guided training,
CVIU(241), 2024, pp. 103952.
Elsevier DOI Code:
WWW Link.
2403
Low-light image enhancement, Coarse-to-fine restoration,
Light-head and heavy-tail network, Retinex theory
BibRef
Guo, L.Q.[Lan-Qing],
Wan, R.J.[Ren-Jie],
Yang, W.H.[Wen-Han],
Kot, A.C.[Alex C.],
Wen, B.[Bihan],
Cross-Image Disentanglement for Low-Light Enhancement in Real World,
CirSysVideo(34), No. 4, April 2024, pp. 2550-2563.
IEEE DOI Code:
WWW Link.
2404
Training, Lighting, Brightness, Reflectivity, Task analysis,
Feature extraction, Image enhancement, Low-light enhancement, disentanglement
BibRef
He, Z.Q.[Zhi-Quan],
Ran, W.[Wu],
Liu, S.L.[Shu-Lin],
Li, K.[Kehua],
Lu, J.[Jiawen],
Xie, C.Y.[Chang-Yong],
Liu, Y.[Yong],
Lu, H.[Hong],
Low-Light Image Enhancement With Multi-Scale Attention and
Frequency-Domain Optimization,
CirSysVideo(34), No. 4, April 2024, pp. 2861-2875.
IEEE DOI
2404
Lighting, Image enhancement, Image color analysis,
Discrete wavelet transforms, Image restoration, Histograms
BibRef
Yu, N.[Nana],
Shi, H.[Hong],
Han, Y.[Yahong],
Joint Correcting and Refinement for Balanced Low-Light Image
Enhancement,
MultMed(26), 2024, pp. 6310-6324.
IEEE DOI
2404
Image color analysis, Lighting, Feature extraction, Brightness,
Image enhancement, Distortion, Visualization,
illumination adjustment
BibRef
Li, Y.Z.[Yue-Zhou],
Xu, R.[Rui],
Niu, Y.Z.[Yu-Zhen],
Guo, W.Z.[Wen-Zhong],
Zhao, T.S.[Tie-Song],
Perceptual Decoupling With Heterogeneous Auxiliary Tasks for Joint
Low-Light Image Enhancement and Deblurring,
MultMed(26), 2024, pp. 6663-6675.
IEEE DOI
2404
Task analysis, Degradation, Image reconstruction,
Image enhancement, Brightness, Image restoration,
image deblurring
BibRef
Guo, L.[Lanqing],
Lin, Y.X.[Yu-Xin],
Li, J.[Jian],
Wen, B.[Bihan],
Exploiting Illumination Knowledge in the Real World for Low-Light
Image Enhancement,
MultMedMag(31), No. 1, January 2024, pp. 33-41.
IEEE DOI
2404
Lighting, Training, Generators, Cameras, Task analysis,
Image enhancement, Benchmark testing, Deep learning, Image quality,
Semisupervised learning
BibRef
Yuan, S.[Shuang],
Li, J.J.[Jin-Jiang],
Ren, L.[Lu],
Chen, Z.[Zheng],
Multi-Frequency Field Perception and Sparse Progressive Network for
low-light image enhancement,
JVCIR(100), 2024, pp. 104133.
Elsevier DOI
2405
Frequency domain scene perception, Sparse enhancement factor,
Iterative progressive structure
BibRef
Li, W.[Wei],
Huang, Y.[Ya],
Zhang, X.Y.[Xin-Yuan],
Han, G.J.[Gui-Jin],
LIIS: Low-light image instance segmentation,
JVCIR(100), 2024, pp. 104116.
Elsevier DOI
2405
Instance segmentation, Low-light image,
Post-processing detail enhancement denoising module,
W-BCNet instance segmentation network
BibRef
Qiao, S.[Sihai],
Chen, R.[Rong],
Progressive feature fusion for SNR-aware low-light image enhancement,
JVCIR(100), 2024, pp. 104148.
Elsevier DOI
2405
Low light enhancement, SNR, Progressive feature fusion,
High frequency information
BibRef
Jin, H.Y.[Hai-Yan],
Li, L.[Long],
Su, H.[Haonan],
Zhang, Y.L.[Yuan-Lin],
Xiao, Z.L.[Zhao-Lin],
Wang, B.[Bin],
Learn to enhance the low-light image via a multi-exposure generation
and fusion method,
JVCIR(100), 2024, pp. 104127.
Elsevier DOI
2405
Multi exposure generation and fusion,
Low light image enhancement, Perceptual importance, Feature fusion
BibRef
Khan, R.[Rizwan],
Mehmood, A.[Atif],
Shahid, F.[Farah],
Zheng, Z.[Zhonglong],
Ibrahim, M.M.[Mostafa M.],
Lit me up: A reference free adaptive low light image enhancement for
in-the-wild conditions,
PR(153), 2024, pp. 110490.
Elsevier DOI
2405
Uneven lighting, Image enhancement, Adaptive learning
BibRef
Zhang, J.Y.[Jing-Yao],
Hao, S.J.[Shi-Jie],
Rao, Y.[Yuan],
Pre-trained low-light image enhancement transformer,
IET-IPR(18), No. 8, 2024, pp. 1967-1984.
DOI Link
2406
image enhancement, image processing
BibRef
Gao, J.X.[Jia-Xin],
Liu, Y.H.[Yao-Hua],
Yue, Z.Y.[Zi-Yu],
Fan, X.[Xin],
Liu, R.S.[Ri-Sheng],
Collaborative brightening and amplification of low-light imagery via
bi-level adversarial learning,
PR(154), 2024, pp. 110558.
Elsevier DOI Code:
WWW Link.
2406
Low-light image, Bi-level optimization, Image enhancement, Deep learning
BibRef
Han, W.W.[Wen-Wu],
Xiao, Y.[Yigai],
Yin, Y.[Yu],
UM-GAN: Underground mine GAN for underground mine low-light image
enhancement,
IET-IPR(18), No. 8, 2024, pp. 2154-2160.
DOI Link
2406
computer vision, image denoising, image enhancement
BibRef
Demir, Y.,
Kaplan, N.H.,
Kucuk, S.,
Severoglu, N.,
Pixel-wise low-light image enhancement based on metropolis theorem,
JVCIR(102), 2024, pp. 104211.
Elsevier DOI
2407
Low-light enhancement, Metropolis theorem,
Multi-scale decomposition, Gamma correction
BibRef
Zhang, Y.T.[Yuan-Tong],
Teng, B.X.[Bao-Xin],
Yang, D.Q.[Dai-Qin],
Chen, Z.Z.[Zhen-Zhong],
Ma, H.C.[Hai-Chuan],
Li, G.[Gang],
Ding, W.P.[Wen-Peng],
Learning a Single Convolutional Layer Model for Low Light Image
Enhancement,
CirSysVideo(34), No. 7, July 2024, pp. 5995-6008.
IEEE DOI Code:
WWW Link.
2407
Lighting, Convolution, Computational modeling, Image enhancement,
Training, Technological innovation, Deep learning,
structural re-parameterization
BibRef
Li, Q.[Qintong],
Ma, Y.[Yong],
Huang, J.[Jun],
Zhang, C.[Can],
Cai, Z.[Zhao],
LELD: Learn enhancement by learning degradation,
IVC(148), 2024, pp. 105102.
Elsevier DOI
2407
Low-light image enhancement, Degradation network,
Generative adversarial network, Retinex theory
BibRef
Yu, N.[Nana],
Wang, J.[Jie],
Shi, H.[Hong],
Zhang, Z.[Zihao],
Han, Y.[Yahong],
Degradation-removed multiscale fusion for low-light salient object
detection,
PR(155), 2024, pp. 110650.
Elsevier DOI Code:
WWW Link.
2408
Salient object detection, Low-light, Image enhancement,
Retinex decomposition, Multiscale adaptive fusion
BibRef
Qu, J.X.[Jing-Xiang],
Liu, R.W.[Ryan Wen],
Gao, Y.[Yuan],
Guo, Y.[Yu],
Zhu, F.[Fenghua],
Wang, F.Y.[Fei-Yue],
Double Domain Guided Real-Time Low-Light Image Enhancement for
Ultra-High-Definition Transportation Surveillance,
ITS(25), No. 8, August 2024, pp. 9550-9562.
IEEE DOI Code:
WWW Link.
2408
BibRef
Wang, W.J.[Wen-Jing],
Luo, R.D.[Run-Dong],
Yang, W.H.[Wen-Han],
Liu, J.Y.[Jia-Ying],
Unsupervised Illumination Adaptation for Low-Light Vision,
PAMI(46), No. 9, September 2024, pp. 5951-5966.
IEEE DOI
2408
Task analysis, Training, Adaptation models, Lighting, Cameras,
Data models, Face recognition, Domain adaptation,
self-supervised learning
BibRef
Jiang, S.Q.[Sheng-Qin],
Mei, Y.[Yongyue],
Wang, P.[Peng],
Liu, Q.S.[Qing-Shan],
Exposure difference network for low-light image enhancement,
PR(156), 2024, pp. 110796.
Elsevier DOI
2408
Low-light image, Image enhancement, Exposure difference, Neural network
BibRef
Lu, X.[Xiao],
Yuan, Y.L.[Yu-Lin],
Liu, X.[Xing],
Wang, L.[Lucai],
Zhou, X.Y.[Xuan-Yu],
Yang, Y.M.[Yi-Min],
Low-Light Salient Object Detection by Learning to Highlight the
Foreground Objects,
CirSysVideo(34), No. 8, August 2024, pp. 7712-7724.
IEEE DOI Code:
WWW Link.
2408
Object detection, Task analysis, Image enhancement, Lighting,
Feature extraction, Training, Dynamic range, datasets
BibRef
Wang, Z.X.[Ze-Xin],
Qingge, L.[Letu],
Pan, Q.Y.[Qing-Yi],
Yang, P.[Pei],
Retinex decomposition based low-light image enhancement by
integrating Swin transformer and U-Net-like architecture,
IET-IPR(18), No. 11, 2024, pp. 3028-3041.
DOI Link
2409
low-light image enhancement, residual connection,
swin transformer, U-Net
BibRef
Manekar, R.[Raunak],
Negrini, E.[Elisa],
Pham, M.[Minh],
Jacobs, D.[Daniel],
Srivastava, J.[Jaideep],
Osher, S.J.[Stanley J.],
Miao, J.W.[Jian-Wei],
Low-Light Phase Retrieval With Implicit Generative Priors,
IP(33), 2024, pp. 4728-4737.
IEEE DOI
2409
Imaging, Diffraction, Noise, Lighting, Image reconstruction, Training,
Optimization, Deep generative models, computational imaging,
zero-shot learning
BibRef
Liang, D.[Dong],
Xu, Z.Y.[Zheng-Yan],
Li, L.[Ling],
Wei, M.Q.[Ming-Qiang],
Chen, S.C.[Song-Can],
PIE: Physics-Inspired Low-Light Enhancement,
IJCV(132), No. 1, January 2024, pp. 3911-3932.
Springer DOI
2409
BibRef
Bernabel, S.A.[Silvano A.],
Agaian, S.S.[Sos S.],
NDELS: A Novel Approach for Nighttime Dehazing, Low-Light
Enhancement, and Light Suppression,
MultMed(26), 2024, pp. 9292-9303.
IEEE DOI
2409
Training, Image color analysis, Lighting, Colored noise,
Image restoration, Image edge detection, Histograms, multiscale retinex
BibRef
Hou, Y.Q.[Yong-Qi],
Yang, B.[Bo],
Semantic attention guided low-light image enhancement with
multi-scale perception,
JVCIR(103), 2024, pp. 104242.
Elsevier DOI
2409
Low-light image enhancement, Semantic guidance,
Attention mechanism, Deep learning
BibRef
Anoop, P.P.,
Deivanathan, R.,
Advancements in low light image enhancement techniques and recent
applications,
JVCIR(103), 2024, pp. 104223.
Elsevier DOI
2409
Low-light image enhancement, Deep learning,
Image processing, Machine learning, Image quality assessment
BibRef
Xue, R.[Rui],
Duan, J.[Jialu],
Du, Z.W.[Zheng-Wei],
MPE-DETR: A multiscale pyramid enhancement network for object
detection in low-light images,
IVC(150), 2024, pp. 105202.
Elsevier DOI Code:
WWW Link.
2409
Object detection, Low-light images, Multiscale pyramid networks
BibRef
Liu, R.W.[Ryan Wen],
Han, C.[Chu],
Huang, Y.H.[Yan-Hong],
Low-light visibility enhancement for improving visual surveillance in
intelligent waterborne transportation systems,
IET-ITS(18), No. 9, 2024, pp. 1632-1651.
DOI Link
2409
image enhancement, image restoration, marine vehicles
BibRef
Wang, X.J.[Xue-Jin],
Huang, L.L.[Lei-Lei],
Chen, H.W.[Hang-Wei],
Jiang, Q.P.[Qiu-Ping],
Weng, S.W.[Shao-Wei],
Shao, F.[Feng],
Benchmark Dataset and Pair-Wise Ranking Method for Quality Evaluation
of Night-Time Image Enhancement,
MultMed(26), 2024, pp. 9436-9449.
IEEE DOI Code:
WWW Link.
2410
Measurement, Image enhancement, Lighting, Feature extraction,
Image quality, Distortion, Benchmark testing,
pair-wise ranking
See also Underwater Image Enhancement Quality Evaluation: Benchmark Dataset and Objective Metric.
BibRef
Ye, D.J.[Dong-Jie],
Chen, B.L.[Bao-Liang],
Wang, S.Q.[Shi-Qi],
Kwong, S.[Sam],
CodedBGT: Code Bank-Guided Transformer for Low-Light Image
Enhancement,
MultMed(26), 2024, pp. 9880-9891.
IEEE DOI
2410
Codes, Image enhancement, Transformers, Lighting, Decoding,
Artificial neural networks, Visualization,
vision transformer
BibRef
Li, F.[Fei],
Wang, C.[Caiju],
Li, X.M.[Xiao-Mao],
Enhancing low-light images via dehazing principles: Essence and
method,
PRL(185), 2024, pp. 167-174.
Elsevier DOI
2410
Low-light image enhancement, Dehazing, Haze formation model, Image inversion
BibRef
Xue, M.L.[Ming-Long],
He, Y.Y.[Yan-Yi],
He, J.H.[Jin-Hong],
Zhong, S.M.[Sen-Ming],
DLDiff: Image Detail-Guided Latent Diffusion Model for Low-Light
Image Enhancement,
SPLetters(31), 2024, pp. 2255-2259.
IEEE DOI
2410
Diffusion models, Noise, Task analysis, Training, Image enhancement,
Feature extraction, Diffusion processes,
latent diffusion models
BibRef
Wang, H.N.[Hao-Ning],
Yang, H.B.[Hong-Bo],
Zhang, Y.[Yang],
Yang, M.H.[Ming-Hao],
Unsupervised Low-Light Image Enhancement via Feature Smoothing and
Curve Regression,
SPLetters(31), 2024, pp. 2475-2479.
IEEE DOI
2410
Lighting, Noise, Reflection, Feature extraction, Noise reduction, Histograms,
Training, Deep learning, image denoising, low-light image enhancement
BibRef
Liu, Y.L.[Yun-Long],
Huang, T.[Tao],
Dong, W.S.[Wei-Sheng],
Wu, F.F.[Fang-Fang],
Li, X.[Xin],
Shi, G.M.[Guang-Ming],
Low-Light Image Enhancement with Multi-stage Residue Quantization and
Brightness-aware Attention,
ICCV23(12106-12115)
IEEE DOI
2401
BibRef
Zhang, F.[Feng],
Xu, B.[Bin],
Li, Z.Q.[Zhi-Qiang],
Liu, X.R.[Xin-Ran],
Lu, Q.B.[Qing-Bo],
Gao, C.X.[Chang-Xin],
Sang, N.[Nong],
Towards General Low-Light Raw Noise Synthesis and Modeling,
ICCV23(10786-10796)
IEEE DOI
2401
BibRef
Liang, J.X.[Jin-Xiu],
Yang, Y.X.[Yi-Xin],
Li, B.[Boyu],
Duan, P.Q.[Pei-Qi],
Xu, Y.[Yong],
Shi, B.X.[Bo-Xin],
Coherent Event Guided Low-Light Video Enhancement,
ICCV23(10581-10591)
IEEE DOI
2401
BibRef
Yi, X.[Xunpeng],
Xu, H.[Han],
Zhang, H.[Hao],
Tang, L.F.[Lin-Feng],
Ma, J.Y.[Jia-Yi],
Diff-Retinex: Rethinking Low-light Image Enhancement with A
Generative Diffusion Model,
ICCV23(12268-12277)
IEEE DOI
2401
BibRef
Zheng, N.S.[Nai-Shan],
Zhou, M.[Man],
Dong, Y.M.[Yan-Meng],
Rui, X.Y.[Xiang-Yu],
Huang, J.[Jie],
Li, C.Y.[Chong-Yi],
Zhao, F.[Feng],
Empowering Low-Light Image Enhancer through Customized Learnable
Priors,
ICCV23(12525-12535)
IEEE DOI Code:
WWW Link.
2401
BibRef
Fu, H.Y.[Hui-Yuan],
Zheng, W.K.[Wen-Kai],
Wang, X.[Xicong],
Wang, J.X.[Jia-Xuan],
Zhang, H.[Heng],
Ma, H.D.[Hua-Dong],
Dancing in the Dark:
A Benchmark towards General Low-light Video Enhancement,
ICCV23(12831-12840)
IEEE DOI Code:
WWW Link.
2401
BibRef
Yang, S.[Shuzhou],
Ding, M.[Moxuan],
Wu, Y.M.[Yan-Min],
Li, Z.[Zihan],
Zhang, J.[Jian],
Implicit Neural Representation for Cooperative Low-light Image
Enhancement,
ICCV23(12872-12881)
IEEE DOI Code:
WWW Link.
2401
BibRef
Wang, Y.L.[Ying-Long],
Liu, Z.[Zhen],
Liu, J.Z.[Jian-Zhuang],
Xu, S.[Songcen],
Liu, S.C.[Shuai-Cheng],
Low-Light Image Enhancement with Illumination-Aware Gamma Correction
and Complete Image Modelling Network,
ICCV23(13082-13091)
IEEE DOI
2401
BibRef
Desai, C.[Chaitra],
Akalwadi, N.[Nikhil],
Joshi, A.[Amogh],
Malagi, S.[Sampada],
Mandi, C.[Chinmayee],
Tabib, R.A.[Ramesh Ashok],
Patil, U.[Ujwala],
Mudenagudi, U.[Uma],
LightNet: Generative Model for Enhancement of Low-Light Images,
WiCV-ICCV23(2223-2232)
IEEE DOI
2401
BibRef
Hashmi, K.A.[Khurram Azeem],
Kallempudi, G.[Goutham],
Stricker, D.[Didier],
Afzal, M.Z.[Muhammamd Zeshan],
FeatEnHancer: Enhancing Hierarchical Features for Object Detection
and Beyond Under Low-Light Vision,
ICCV23(6702-6712)
IEEE DOI
2401
BibRef
Wang, Y.F.[Yu-Fei],
Yu, Y.[Yi],
Yang, W.H.[Wen-Han],
Guo, L.Q.[Lan-Qing],
Chau, L.P.[Lap-Pui],
Kot, A.C.[Alex C.],
Wen, B.[Bihan],
ExposureDiffusion: Learning to Expose for Low-light Image Enhancement,
ICCV23(12404-12414)
IEEE DOI Code:
WWW Link.
2401
BibRef
Cai, Y.H.[Yuan-Hao],
Bian, H.[Hao],
Lin, J.[Jing],
Wang, H.Q.[Hao-Qian],
Timofte, R.[Radu],
Zhang, Y.[Yulun],
Retinexformer: One-stage Retinex-based Transformer for Low-light
Image Enhancement,
ICCV23(12470-12479)
IEEE DOI Code:
WWW Link.
2401
BibRef
Choudhary, R.[Rohit],
Reddy, T.H.[T Harshith],
Sharma, M.[Mansi],
ELEGAN: An Efficient Low Light Enhancement GAN for Unpaired
Supervision,
ICIP23(3105-3109)
IEEE DOI
2312
BibRef
Ooi, X.P.[Xin Peng],
Chan, C.S.[Chee Seng],
LLDE: Enhancing Low-Light Images with Diffusion Model,
ICIP23(1305-1309)
IEEE DOI Code:
WWW Link.
1806
BibRef
Yi, X.[Xunpeng],
Wang, Y.X.[Yu-Xuan],
Zhao, Y.Z.[Yi-Zhen],
Yan, J.[Jia],
Zhang, W.X.[Wei-Xia],
Llieformer: A Low-Light Image Enhancement Transformer Network with a
Degraded Restoration Model,
ICIP23(1195-1199)
IEEE DOI Code:
WWW Link.
2312
BibRef
Kuang, H.[Haowei],
Huang, H.F.[Hao-Feng],
Yang, W.H.[Wen-Han],
Liu, J.Y.[Jia-Ying],
Flash Compensated Low-Light Enhancement Via Hierarchical Network
Prediction,
ICIP23(3115-3119)
IEEE DOI
2312
BibRef
Wei, X.J.[Xin-Jie],
Chang, K.[Kan],
Li, G.Q.[Gui-Qing],
Huang, M.Y.[Meng-Yuan],
Qin, Q.P.[Qing-Pao],
DLEN: Deep Laplacian Enhancement Networks for Low-Light Images,
ICIP23(2120-2124)
IEEE DOI Code:
WWW Link.
2312
BibRef
Huang, Z.[Zhuo],
Zhu, M.[Miaoxi],
Xia, X.B.[Xiao-Bo],
Shen, L.[Li],
Yu, J.[Jun],
Gong, C.[Chen],
Han, B.[Bo],
Du, B.[Bo],
Liu, T.L.[Tong-Liang],
Robust Generalization Against Photon-Limited Corruptions via
Worst-Case Sharpness Minimization,
CVPR23(16175-16185)
IEEE DOI
2309
BibRef
Sanghvi, Y.[Yash],
Mao, Z.Y.[Zhi-Yuan],
Chan, S.H.[Stanley H.],
Structured Kernel Estimation for Photon-Limited Deconvolution,
CVPR23(9863-9872)
IEEE DOI
2309
WWW Link.
BibRef
Wu, Y.H.[Yu-Hui],
Pan, C.[Chen],
Wang, G.Q.[Guo-Qing],
Yang, Y.[Yang],
Wei, J.[Jiwei],
Li, C.Y.[Chong-Yi],
Shen, H.T.[Heng Tao],
Learning Semantic-Aware Knowledge Guidance for Low-Light Image
Enhancement,
CVPR23(1662-1671)
IEEE DOI
2309
BibRef
Cao, Y.[Yue],
Liu, M.[Ming],
Liu, S.[Shuai],
Wang, X.T.[Xiao-Tao],
Lei, L.[Lei],
Zuo, W.M.[Wang-Meng],
Physics-Guided ISO-Dependent Sensor Noise Modeling for Extreme
Low-Light Photography,
CVPR23(5744-5753)
IEEE DOI
2309
BibRef
Xu, X.G.[Xiao-Gang],
Wang, R.X.[Rui-Xing],
Lu, J.B.[Jiang-Bo],
Low-Light Image Enhancement via Structure Modeling and Guidance,
CVPR23(9893-9903)
IEEE DOI
2309
BibRef
Fu, H.Y.[Hui-Yuan],
Zheng, W.K.[Wen-Kai],
Meng, X.Y.[Xiang-Yu],
Wang, X.[Xin],
Wang, C.M.[Chuan-Ming],
Ma, H.D.[Hua-Dong],
You Do Not Need Additional Priors or Regularizers in Retinex-Based
Low-Light Image Enhancement,
CVPR23(18125-18134)
IEEE DOI
2309
BibRef
Fu, Z.Q.[Zhen-Qi],
Yang, Y.[Yan],
Tu, X.T.[Xiao-Tong],
Huang, Y.[Yue],
Ding, X.H.[Xing-Hao],
Ma, K.K.[Kai-Kuang],
Learning a Simple Low-Light Image Enhancer from Paired Low-Light
Instances,
CVPR23(22252-22261)
IEEE DOI
2309
BibRef
Lee, S.[Sunhyeok],
Jang, D.[Donggon],
Kim, D.S.[Dae-Shik],
Temporally Averaged Regression for Semi-Supervised Low-Light Image
Enhancement,
UG23(4208-4217)
IEEE DOI
2309
BibRef
Özcan, M.[Mustafa],
Ergezer, H.[Hamza],
Ayazoglu, M.[Mustafa],
FLIGHT Mode On: A Feather-Light Network for Low-Light Image
Enhancement,
UG23(4226-4235)
IEEE DOI
2309
BibRef
Berral-Soler, R.[Rafael],
Muñoz-Salinas, R.[Rafael],
Medina-Carnicer, R.[Rafael],
Marín-Jiménez, M.J.[Manuel J.],
Deeparuco: Marker Detection and Classification in Challenging Lighting
Conditions,
IbPRIA23(199-210).
Springer DOI
2307
BibRef
Chen, X.Y.[Xin-Yu],
Yu, Y.[Yantao],
Image Illumination Enhancement for Construction Worker Pose Estimation
in Low-light Conditions,
CVCivil22(147-162).
Springer DOI
2304
BibRef
Wang, H.D.[Hao-Dian],
Wang, Y.[Yang],
Cao, Y.[Yang],
Zha, Z.J.[Zheng-Jun],
Fusion-Based Low-Light Image Enhancement,
MMMod23(I: 121-133).
Springer DOI
2304
BibRef
Batziou, E.[Elissavet],
Ioannidis, K.[Konstantinos],
Patras, I.[Ioannis],
Vrochidis, S.[Stefanos],
Kompatsiaris, I.[Ioannis],
Low-light Image Enhancement Based on U-net and Haar Wavelet Pooling,
MMMod23(II: 510-522).
Springer DOI
2304
BibRef
Li, Y.H.[Yu-Hang],
Cai, F.F.[Fei-Fan],
Tu, Y.F.[Yi-Fei],
Ding, Y.D.[You-Dong],
Low-light Image Enhancement Under Non-uniform Dark,
MMMod23(II: 190-201).
Springer DOI
2304
BibRef
Nguyen, H.[Hue],
Tran, D.[Diep],
Nguyen, K.[Khoi],
Nguyen, R.[Rang],
PSENet: Progressive Self-Enhancement Network for Unsupervised
Extreme-Light Image Enhancement,
WACV23(1756-1765)
IEEE DOI
2302
Training, Measurement, Codes, Lighting, Face detection,
Image enhancement
BibRef
Lamba, M.[Mohit],
Kumar, M.V.A.S.[M V A Suhas],
Mitra, K.[Kaushik],
Real-Time Restoration of Dark Stereo Images,
WACV23(4903-4913)
IEEE DOI
2302
Visualization, Convolution, Estimation, Real-time systems,
Light fields, Applications: Commercial/retail, Robotics
BibRef
Duan, B.J.[Bing-Jie],
Wang, C.[Chao],
Li, Y.Y.[Yan-Yun],
NonReference Mapping Net,
ICIVC22(718-724)
IEEE DOI
2301
Training, Image quality, Visualization, Image color analysis,
Nonlinear distortion, Object detection, Task analysis,
NonReference mapping
BibRef
Liu, B.[Bokun],
Wei, J.Y.[Jun-Yu],
Su, S.J.[Shao-Jing],
Tong, X.Z.[Xiao-Zhong],
Research on Task-Driven Dual-Light Image Fusion and Enhancement
Method under Low Illumination,
ICIVC22(523-530)
IEEE DOI
2301
Visualization, Roads, Semantics, Lighting, Object detection,
Propagation losses, Reliability, image fusion and enhancement,
low illumination
BibRef
Quan, J.C.[Jin-Cheng],
Jin, H.M.[Hong-Mei],
Li, Z.L.[Zhan-Li],
Wen, Z.[Zi],
Low Illumination Image Enhancement Algorithm Based on HSV-RNET,
ICIVC22(531-536)
IEEE DOI
2301
Smoothing methods, Image color analysis, Image edge detection,
Noise reduction, Lighting, Distortion, Visual effects, Retinex,
low-light images
BibRef
Wei, X.L.[Xiao-Long],
Sun, J.[Jian],
Cai, Y.[Yulu],
Ma, A.[Aiyong],
Su, W.[Wei],
Zero-DCE with HSV loss for Low-Light Image Enhancement,
ICIVC22(537-541)
IEEE DOI
2301
Image color analysis, Surveillance, Brightness, Estimation,
Reconnaissance, Benchmark testing, Image restoration, Zero-DCE, HSV, enhancement
BibRef
Liu, M.H.[Ming-Hao],
Luo, J.H.[Jia-Hao],
Zhang, X.H.[Xiao-Han],
Liu, Y.[Yang],
Davis, J.[James],
Low-light Image Enhancement Using Chain-Consistent Adversarial
Networks,
ICPR22(713-719)
IEEE DOI
2212
Training, Measurement, Image quality, Supervised learning,
Training data, Imaging, Generators
BibRef
Xiong, W.[Wei],
Liu, D.[Ding],
Shen, X.H.[Xiao-Hui],
Fang, C.[Chen],
Luo, J.B.[Jie-Bo],
Unsupervised Low-light Image Enhancement with Decoupled Networks,
ICPR22(457-463)
IEEE DOI
2212
Training, Adaptation models, Noise reduction, Lighting,
Pattern recognition, Task analysis, Image enhancement
BibRef
Hsu, P.H.[Po-Hao],
Lin, C.T.[Che-Tsung],
Ng, C.C.[Chun Chet],
Kew, J.L.[Jie Long],
Tan, M.Y.[Mei Yih],
Lai, S.H.[Shang-Hong],
Chan, C.S.[Chee Seng],
Zach, C.[Christopher],
Extremely Low-Light Image Enhancement with Scene Text Restoration,
ICPR22(317-323)
IEEE DOI
2212
Learning systems, Image quality, Image edge detection,
Image restoration, Pattern recognition, Image enhancement, Image reconstruction
BibRef
Chen, Z.L.[Zi-Long],
Liang, Y.L.[Ya-Ling],
Du, M.H.[Ming-Hui],
Attention-based Broad Self-guided Network for Low-light Image
Enhancement,
ICPR22(31-38)
IEEE DOI
2212
Wavelet transforms, Runtime, Stacking, Object detection,
Benchmark testing, Feature extraction, Data mining
BibRef
Xu, Z.W.[Zi-Wei],
Wang, W.K.[Wei-Kang],
Cui, Z.K.[Ze-Kun],
Wang, C.[Chao],
A Low-light Image Enhancement Algorithm Based on Optimized
Multi-illumination Fusion,
ICIVC22(549-554)
IEEE DOI
2301
Smoothing methods, Filtering, Heuristic algorithms, Brightness,
Lighting, Optimization methods, Dynamic range, adaptive threshold
BibRef
Guo, J.[Jiacen],
Jin, X.[Xin],
Chen, W.L.[Wei-Lin],
Wang, C.[Chao],
A Novel Low-light Image Enhancement Algorithm Based on Information
Assistance,
ICPR22(3865-3871)
IEEE DOI
2212
Image color analysis, Lighting, Distortion, Pattern recognition,
Optimal matching, Image enhancement
BibRef
Fan, C.M.[Chi-Mao],
Liu, T.J.[Tsung-Jung],
Liu, K.H.[Kuan-Hsien],
Half Wavelet Attention on M-Net+ for Low-Light Image Enhancement,
ICIP22(3878-3882)
IEEE DOI
2211
Measurement, Visualization, Image segmentation, Wavelet domain,
Semantics, Neural networks, Image enhancement, hierarchical, M-Net,
attention mechanism
BibRef
Lecert, A.[Arthur],
Fraisse, R.[Renaud],
Roumy, A.[Aline],
Guillemot, C.[Christine],
A New Regularization for Retinex Decomposition of Low-Light Images,
ICIP22(906-910)
IEEE DOI
2211
Measurement, Lighting, Image restoration, Image enhancement,
Light sources, Low light enhancement, Image decomposition,
Neural Networks
BibRef
Mukaida, M.[Mashiho],
Ueda, Y.[Yoshiaki],
Suetake, N.[Noriaki],
Low-Light Image Enhancement Method by Using a Modified Gamma
Transform for Convex Combination Coefficients,
ICIP22(2866-2870)
IEEE DOI
2211
Histograms, Smoothing methods, Image color analysis, Transforms,
Information filters, Computational efficiency, Image enhancement,
Histogram Specification
BibRef
Gao, H.Y.[Hao-Yu],
Zhang, L.[Lin],
Zhang, S.[Shunli],
Recurrent Attentive Decomposition Network for Low-Light Image
Enhancement,
ICIP22(3818-3822)
IEEE DOI
2211
Visualization, Image recognition, Image color analysis, Distortion,
Reflection, Image decomposition, Image restoration,
Recurrent Attentive Decomposition Network
BibRef
Monakhova, K.[Kristina],
Richter, S.R.[Stephan R.],
Waller, L.[Laura],
Koltun, V.[Vladlen],
Dancing under the stars: video denoising in starlight,
CVPR22(16220-16230)
IEEE DOI
2210
Semiconductor device modeling, Noise reduction, Lighting, Stars,
Cameras, Quality assessment, Pattern recognition,
Physics-based vision and shape-from-X
BibRef
Wu, W.H.[Wen-Hui],
Weng, J.[Jian],
Zhang, P.P.[Ping-Ping],
Wang, X.[Xu],
Yang, W.H.[Wen-Han],
Jiang, J.M.[Jian-Min],
URetinex-Net: Retinex-based Deep Unfolding Network for Low-light
Image Enhancement,
CVPR22(5891-5900)
IEEE DOI
2210
Reflectivity, Learning systems, Adaptation models, Codes,
Noise reduction, Lighting, Low-level vision
BibRef
Ma, L.[Long],
Ma, T.Y.[Teng-Yu],
Liu, R.S.[Ri-Sheng],
Fan, X.[Xin],
Luo, Z.X.[Zhong-Xuan],
Toward Fast, Flexible, and Robust Low-Light Image Enhancement,
CVPR22(5627-5636)
IEEE DOI
2210
Training, Adaptation models, Visualization, Image segmentation,
Computational modeling, Semantics, Lighting, Low-level vision
BibRef
Zhang, Z.[Zhao],
Zheng, H.[Huan],
Hong, R.C.[Ri-Chang],
Xu, M.L.[Ming-Liang],
Yan, S.C.[Shui-Cheng],
Wang, M.[Meng],
Deep Color Consistent Network for Low-Light Image Enhancement,
CVPR22(1889-1898)
IEEE DOI
2210
Image quality, Histograms, Image color analysis, Lighting,
Collaboration, Color, Low-level vision,
Deep learning architectures and techniques
BibRef
Xu, X.G.[Xiao-Gang],
Wang, R.X.[Rui-Xing],
Fu, C.W.[Chi-Wing],
Jia, J.Y.[Jia-Ya],
SNR-Aware Low-light Image Enhancement,
CVPR22(17693-17703)
IEEE DOI
2210
Photography, Convolutional codes, Convolution, Semantics,
Transformers, Pattern recognition, Noise measurement, Low-level vision
BibRef
Morawski, I.[Igor],
Chen, Y.A.[Yu-An],
Lin, Y.S.[Yu-Sheng],
Dangi, S.[Shusil],
He, K.[Kai],
Hsu, W.H.[Winston H.],
GenISP: Neural ISP for Low-Light Machine Cognition,
NTIRE22(629-638)
IEEE DOI
2210
Image sensors, Image color analysis, Pipelines, Detectors,
Object detection, Cameras, Cognition
BibRef
Fu, Z.C.[Zhi-Cheng],
Song, M.[Miao],
Ma, C.[Chao],
Nasti, J.[Joe],
Tyagi, V.[Vivek],
Lloyd, G.[Grant],
Tang, W.[Wei],
An Efficient Hybrid Model for Low-light Image Enhancement in Mobile
Devices,
MobileAI22(3056-3065)
IEEE DOI
2210
Estimation, Predictive models, Software,
Real-time systems, Hardware, Convolutional neural networks
BibRef
Qi, J.Z.[Jing-Zhong],
Qi, N.[Na],
Zhu, Q.[Qing],
SUnet++: Joint Demosaicing and Denoising of Extreme Low-Light Raw Image,
MMMod22(II:171-181).
Springer DOI
2203
BibRef
Jin, S.[Shuang],
Qi, N.[Na],
Zhu, Q.[Qing],
Ouyang, H.R.[Hao-Ran],
Progressive GAN-Based Transfer Network for Low-Light Image Enhancement,
MMMod22(II:292-304).
Springer DOI
2203
BibRef
Zheng, C.J.[Chuan-Jun],
Shi, D.M.[Da-Ming],
Shi, W.[Wentian],
Adaptive Unfolding Total Variation Network for Low-Light Image
Enhancement,
ICCV21(4419-4428)
IEEE DOI
2203
Adaptation models, Adaptive systems, TV, Noise reduction, Pipelines,
Estimation, Minimization, Low-level and physics-based vision,
BibRef
Kim, B.[Bomi],
Lee, S.[Sunhyeok],
Kim, N.[Nahyun],
Jang, D.G.[Dong-Gon],
Kim, D.S.[Dae-Shik],
Learning Color Representations for Low-Light Image Enhancement,
WACV22(904-912)
IEEE DOI
2202
Training, Representation learning, Histograms, Visualization,
Image color analysis, Supervised learning, Image restoration,
Image Processing -> Image Restoration Deep Learning
BibRef
Lamba, M.[Mohit],
Mitra, K.[Kaushik],
Fast and Efficient Restoration of Extremely Dark Light Fields,
WACV22(3152-3161)
IEEE DOI
2202
Geometry, Fuses,
Estimation, Light fields, Distance measurement,
Image and Video Synthesis Low-level and Physics-based Vision
BibRef
Zheng, S.[Shen],
Gupta, G.[Gaurav],
Semantic-Guided Zero-Shot Learning for Low-Light Image/Video
Enhancement,
RWSurvil22(581-590)
IEEE DOI
2202
Photography, Image segmentation, Convolution,
Motion segmentation, Conferences, Semantics
BibRef
Akai, M.[Masato],
Ueda, Y.[Yoshiaki],
Koga, T.[Takanori],
Suetake, N.[Noriaki],
A Single Backlit Image Enhancement Method for Improvement of
Visibility of Dark Part,
ICIP21(1659-1663)
IEEE DOI
2201
Histograms, Task analysis, Image enhancement, Backlit image,
image enhancement, weight map, alpha blending
BibRef
Zhao, L.C.[Ling-Chao],
Gong, X.L.[Xiao-Lin],
Liu, K.[Kaihua],
Wang, J.[Jian],
Zhao, B.[Bai],
Liu, Y.[Yu],
Color Channel Fusion Network for Low-Light Image Enhancement,
ICIP21(1654-1658)
IEEE DOI
2201
Training, Image color analysis, Lighting, Image reconstruction,
Image enhancement, low-light image enhancement, deep learning,
detail enhancement
BibRef
Guo, L.Q.[Lan-Qing],
Wan, R.J.[Ren-Jie],
Su, G.M.[Guan-Ming],
Kot, A.C.[Alex C.],
Wen, B.[Bihan],
Multi-Scale Feature Guided Low-Light Image Enhancement,
ICIP21(554-558)
IEEE DOI
2201
Visualization, Inverse problems, Lighting, Object detection,
Feature extraction, Generative adversarial networks, Low-Light,
Unsupervised Learning
BibRef
Tang, P.L.[Peng-Liang],
Guo, X.Q.[Xiao-Qiang],
Ju, G.D.[Guo-Dong],
Shen, L.H.[Liang-Heng],
Men, A.[Aidong],
Integration-and-Diffusion Network for Low-Light Image Enhancement,
ICIP21(1664-1668)
IEEE DOI
2201
Learning systems, Image color analysis, Image enhancement,
Image reconstruction, Signal to noise ratio, Photonics,
color recovery
BibRef
Wu, Q.[Qi],
Qin, M.L.[Mao-Ling],
Song, J.Q.[Jing-Qi],
Liu, L.[Li],
An Improved Method of Low Light Image Enhancement Based on Retinex,
ICIVC21(233-241)
IEEE DOI
2112
Lighting, Reflection, Image decomposition, Feeds, Task analysis,
Image enhancement, low light, image enhancement, Retinex
BibRef
Wang, W.J.[Wen-Jing],
Yang, W.H.[Wen-Han],
Liu, J.Y.[Jia-Ying],
HLA-Face: Joint High-Low Adaptation for Low Light Face Detection,
CVPR21(16190-16199)
IEEE DOI
2111
Training, Annotations, Face recognition, Surveillance, Pipelines,
Buildings, Detectors
BibRef
Zhang, F.[Fan],
Li, Y.[Yu],
You, S.D.[Shao-Di],
Fu, Y.[Ying],
Learning Temporal Consistency for Low Light Video Enhancement from
Single Images,
CVPR21(4965-4974)
IEEE DOI
2111
Training, Computational modeling, Video sequences,
Stability analysis, Planning, Pattern recognition
BibRef
Liu, R.S.[Ri-Sheng],
Ma, L.[Long],
Zhang, J.[Jiaao],
Fan, X.[Xin],
Luo, Z.X.[Zhong-Xuan],
Retinex-inspired Unrolling with Cooperative Prior Architecture Search
for Low-light Image Enhancement,
CVPR21(10556-10565)
IEEE DOI
2111
Deep learning, Architecture, Computational modeling, Lighting,
Search problems, Pattern recognition
BibRef
Moseley, B.[Ben],
Bickel, V.[Valentin],
López-Francos, I.G.[Ignacio G.],
Rana, L.[Loveneesh],
Extreme Low-Light Environment-Driven Image Denoising over Permanently
Shadowed Lunar Regions with a Physical Noise Model,
CVPR21(6313-6323)
IEEE DOI
2111
Training, Solid modeling, Moon,
Noise reduction, Training data, Ray tracing
BibRef
Qiu, Y.S.[Yan-Sheng],
Chen, J.[Jun],
Wang, X.[Xiao],
Jang, K.[Kui],
Illuminate Low-Light Image via Coarse-to-Fine Multi-Level Network,
MMMod21(I:253-264).
Springer DOI
2106
BibRef
Wang, L.W.[Li-Wen],
Siu, W.C.[Wan-Chi],
Liu, Z.S.[Zhi-Song],
Li, C.T.[Chu-Tak],
Lun, D.P.K.[Daniel Pak-Kong],
Video Lightening with Dedicated CNN Architecture,
ICPR21(6447-6454)
IEEE DOI
2105
Measurement, Legged locomotion, Visualization, Uncertainty, Roads,
Transfer learning, Lighting, Low-light video enhancement, deep learning
BibRef
Guo, H.F.[Hai-Feng],
Lu, T.[Tong],
Wu, Y.[Yirui],
Dynamic Low-Light Image Enhancement for Object Detection via
End-to-End Training,
ICPR21(5611-5618)
IEEE DOI
2105
Training, Image quality, Lighting, Object detection,
Detectors, Pattern recognition, Low-Light Image Enhancement, Object Detection
BibRef
Song, Y.[Yuda],
Zhu, Y.F.[Yun-Fang],
Du, X.[Xin],
Automatical Enhancement and Denoising of Extremely Low-light Images,
ICPR21(858-865)
IEEE DOI
2105
Histograms, Noise reduction, Neural networks, Lighting, Manuals,
Image sampling, Image restoration
BibRef
Vogt, C.[Carson],
Lyu, G.[Geng],
Subr, K.[Kartic],
Lightless Fields: Enhancement and Denoising of Light-deficient Light
Fields,
ISVC20(I:383-396).
Springer DOI
2103
BibRef
Guo, P.[Peiyao],
Ma, Z.[Zhan],
Low-light Color Imaging via Dual Camera Acquisition,
ACCV20(II:150-167).
Springer DOI
2103
BibRef
Loh, Y.P.[Yuen Peng],
Exploring the Contributions of Low-light Image Enhancement to
Network-based Object Detection,
MOI2QDN20(655-669).
Springer DOI
2103
BibRef
Azizi, Z.,
Lei, X.,
Kuo, C.C.J.,
Noise-Aware Texture-Preserving Low-Light Enhancement,
VCIP20(443-446)
IEEE DOI
2102
Lighting, Noise reduction, Noise measurement, Image color analysis,
Image edge detection, Optimization, Estimation,
denoising
BibRef
Ngee Bow, N.C.,
Tran, V.H.,
Kerdsiri, P.,
Loh, Y.P.,
Huang, C.C.,
DEN: Disentanglement and Enhancement Networks for Low Illumination
Images,
VCIP20(419-422)
IEEE DOI
2102
Lighting, Feature extraction, Reflectivity, Image enhancement,
Finite element analysis, Convolution, Tuning,
multi-branch enhancement network
BibRef
Xi, L.,
Chen, W.,
Zhao, C.,
Wu, X.,
Wang, J.,
Image Enhancement for Remote Photoplethysmography in a Low-Light
Environment,
FG20(1-7)
IEEE DOI
2102
Gesture recognition, Face recognition
BibRef
Triantafyllidou, D.[Danai],
Moran, S.[Sean],
McDonagh, S.[Steven],
Parisot, S.[Sarah],
Slabaugh, G.[Gregory],
Low Light Video Enhancement Using Synthetic Data Produced with an
Intermediate Domain Mapping,
ECCV20(XIII:103-119).
Springer DOI
2011
BibRef
Chi, Y.H.[Yi-Heng],
Gnanasambandam, A.[Abhiram],
Koltun, V.[Vladlen],
Chan, S.H.[Stanley H.],
Dynamic Low-light Imaging with Quanta Image Sensors,
ECCV20(XXI:122-138).
Springer DOI
2011
BibRef
Ke, X.[Xue],
Lin, W.[Wei],
Chen, G.J.[Gao-Jie],
Chen, Q.[Quan],
Qi, X.Z.[Xian-Zhi],
Ma, J.[Jie],
EDLLIE-Net: Enhanced Deep Convolutional Networks for Low-Light Image
Enhancement,
ICIVC20(59-68)
IEEE DOI
2009
Image enhancement, Task analysis, Feature extraction, Lighting,
Image color analysis, Artificial intelligence, Automation,
EDLLIE-Net
BibRef
Xu, K.,
Yang, X.,
Yin, B.,
Lau, R.W.H.,
Learning to Restore Low-Light Images via
Decomposition-and-Enhancement,
CVPR20(2278-2287)
IEEE DOI
2008
Noise measurement, Image color analysis, Colored noise,
Image enhancement, Lighting, Integrated circuit modeling, Noise reduction
BibRef
Atoum, Y.,
Ye, M.,
Ren, L.,
Tai, Y.,
Liu, X.,
Color-wise Attention Network for Low-light Image Enhancement,
NTIRE20(2130-2139)
IEEE DOI
2008
Image color analysis, Noise reduction, Task analysis,
Colored noise, Lighting, Frequency modulation, Computer vision
BibRef
Liba, O.,
Movshovitz-Attias, Y.,
Cai, L.,
Pritch, Y.,
Tsai, Y.,
Chen, H.,
Eban, E.,
Barron, J.T.,
Sky Optimization: Semantically aware image processing of skies in
low-light photography,
NTIRE20(2230-2238)
IEEE DOI
2008
Image segmentation, Image resolution, Mobile handsets,
Neural networks, Cameras, Image color analysis, Colored noise
BibRef
Wang, W.,
Chen, X.,
Yang, C.,
Li, X.,
Hu, X.,
Yue, T.,
Enhancing Low Light Videos by Exploring High Sensitivity Camera Noise,
ICCV19(4110-4118)
IEEE DOI
2004
cameras, image capture, image denoising, image enhancement,
recurrent neural nets, video signal processing, digital cameras,
Gaussian distribution
BibRef
Wang, R.X.[Rui-Xing],
Zhang, Q.[Qing],
Fu, C.W.[Chi-Wing],
Shen, X.Y.[Xiao-Yong],
Zheng, W.S.[Wei-Shi],
Jia, J.Y.[Jia-Ya],
Underexposed Photo Enhancement Using Deep Illumination Estimation,
CVPR19(6842-6850).
IEEE DOI
2002
BibRef
Kanellakis, C.[Christoforos],
Karvelis, P.[Petros],
Nikolakopoulos, G.[George],
Image Enhancing in Poorly Illuminated Subterranean Environments for Mav
Applications: A Comparison Study,
CVS19(511-520).
Springer DOI
1912
BibRef
Cheng, Y.,
Yan, J.,
Wang, Z.,
Enhancement of Weakly Illuminated Images by Deep Fusion Networks,
ICIP19(924-928)
IEEE DOI
1910
weakly illuminated image enhancement, Retinex,
image fusion, convolution neural network
BibRef
Kim, G.,
Kwon, D.,
Kwon, J.,
Low-Lightgan: Low-Light Enhancement Via Advanced Generative
Adversarial Network With Task-Driven Training,
ICIP19(2811-2815)
IEEE DOI
1910
Low-light enhancement, task-driven training set, GANs, spectral normalization
BibRef
Ghosh, S.,
Chaudhury, K.N.,
Kernel-Based Image Filtering: Fast Algorithms and Applications,
ICIP19(3018-3019)
IEEE DOI
1910
low-light enhancement, retinex, bilateral filter,
Fourier approximation, fast algorithm
BibRef
Ghosh, S.,
Chaudhury, K.N.,
Fast Bright-Pass Bilateral Filtering for Low-Light Enhancement,
ICIP19(205-209)
IEEE DOI
1910
low-light enhancement, retinex, bilateral filter,
Fourier approximation, fast algorithm
BibRef
Malik, S.,
Soundararajan, R.,
A Model Learning Approach For Low Light Image Restoration,
ICIP20(1033-1037)
IEEE DOI
2011
BibRef
Earlier:
Llrnet: A Multiscale Subband Learning Approach for Low Light Image
Restoration,
ICIP19(779-783)
IEEE DOI
1910
Image restoration, Noise reduction, Noise measurement, Distortion,
Computational modeling, Training, Cameras, Contrast enhancement,
CNN.
Contrast enhancement, low light enhancement, denoising. Laplacian pyramid
BibRef
Dhara, S.K.,
Sen, D.,
Low Light Image Enhancement Using Grover's Algorithm on Superposed
Luminance Levels,
ICIP18(1113-1117)
IEEE DOI
1809
Histograms, Image enhancement, Lighting, Image color analysis,
Probability density function, Proposals,
Quantum probability
BibRef
Rupapara, P.,
Rangavajjula, A.,
Jain, A.,
Low complexity image fusion in bayer domain using a monochrome sensor
and bayer sensor,
ICIP17(1980-1984)
IEEE DOI
1803
Erbium, Bayer image fusion, Dual sensor system, Low light photography
BibRef
Tao, L.[Li],
Zhu, C.[Chuang],
Xiang, G.Q.[Guo-Qing],
Li, Y.[Yuan],
Jia, H.Z.[Hui-Zhu],
Xie, X.D.[Xiao-Dong],
LLCNN: A Convolutional Neural Network for Low-Light Image Enhancement,
VCIP17(1-4)
IEEE DOI
1804
convolution, feature extraction, feedforward neural nets,
image enhancement, image texture, CNN based method,
low-light image
BibRef
Tao, L.,
Zhu, C.,
Song, J.,
Lu, T.,
Jia, H.,
Xie, X.,
Low-light image enhancement using CNN and bright channel prior,
ICIP17(3215-3219)
IEEE DOI
1803
Adaptation models, Atmospheric modeling, Filtering theory,
Image color analysis, Mathematical model, Scattering, CNN,
low-light model
BibRef
Shi, W.,
Chen, C.,
Jiang, F.,
Zhao, D.,
Shen, W.,
Group-based sparse representation for low lighting image enhancement,
ICIP16(4082-4086)
IEEE DOI
1610
Decision support systems
BibRef
Kim, Y.[Youngbae],
Koh, Y.J.[Yeong Jun],
Lee, C.[Chulwoo],
Kim, S.H.[Se-Hoon],
Kim, C.S.[Chang-Su],
Dark image enhancement based onpairwise target contrast and
multi-scale detail boosting,
ICIP15(1404-1408)
IEEE DOI
1512
Dark image enhancement
BibRef
Arun, M.,
Rajagopalan, A.N.,
Hand-held low-light photography with exposure bracketing,
ICIP16(1749-1753)
IEEE DOI
1610
Cameras
BibRef
Fotiadou, K.[Konstantina],
Tsagkatakis, G.[Grigorios],
Tsakalides, P.[Panagiotis],
Low Light Image Enhancement via Sparse Representations,
ICIAR14(I: 84-93).
Springer DOI
1410
BibRef
Zhang, X.D.[Xiang-Dong],
Shen, P.[Peiyi],
Luo, L.[Lingli],
Zhang, L.[Liang],
Song, J.[Juan],
Enhancement and noise reduction of very low light level images,
ICPR12(2034-2037).
WWW Link.
1302
BibRef
Matsui, S.[Sosuke],
Okabe, T.[Takahiro],
Shimano, M.[Mihoko],
Sato, Y.[Yoichi],
Image Enhancement of Low-Light Scenes with Near-Infrared Flash Images,
ACCV09(I: 213-223).
Springer DOI
0909
BibRef
Mohanty, K.K.,
Gellaboina, M.K.,
Enhancement of low light image based on Gaussian Mixture Modeling,
EUVIP10(232-236).
IEEE DOI
1110
BibRef
Tao, L.[Li],
Ngo, H.[Hau],
Zhang, M.[Ming],
Livingston, A.,
Asari, V.K.,
A multisensor image fusion and enhancement system for assisting drivers
in poor lighting conditions,
AIPR05(106-113).
IEEE DOI
0510
See also Illuminance-Reflectance Model for Nonlinear Enhancement of Color Images, An.
BibRef
Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Night Time Processing .