Yang, H.[Huan],
Fang, Y.M.[Yu-Ming],
Lin, W.S.[Wei-Si],
Perceptual Quality Assessment of Screen Content Images,
IP(24), No. 11, November 2015, pp. 4408-4421.
IEEE DOI
1509
image processing
See also Saliency-Guided Quality Assessment of Screen Content Images.
BibRef
Fang, Y.M.[Yu-Ming],
Yan, J.B.[Jie-Bin],
Li, L.D.[Lei-Da],
Wu, J.J.[Jin-Jian],
Lin, W.S.[Wei-Si],
No Reference Quality Assessment for Screen Content Images With Both
Local and Global Feature Representation,
IP(27), No. 4, April 2018, pp. 1600-1610.
IEEE DOI
1802
feature extraction, gradient methods, image representation,
image texture, regression analysis, support vector machines, HVS,
visual quality assessment
BibRef
Li, Q.H.[Qiao-Hong],
Lin, W.S.[Wei-Si],
Fang, Y.M.[Yu-Ming],
Zhang, X.F.[Xin-Feng],
Zhang, Y.B.[Ya-Bin],
No-Reference Image Quality Assessment Based on Local Region
Statistics,
VCIP16(1-4)
IEEE DOI
1701
Databases
See also Multiple-Level Feature-Based Measure for Retargeted Image Quality.
BibRef
Chen, B.L.[Bao-Liang],
Zhu, H.W.[Han-Wei],
Zhu, L.Y.[Ling-Yu],
Wang, S.Q.[Shi-Qi],
Kwong, S.[Sam],
Deep Feature Statistics Mapping for Generalized Screen Content Image
Quality Assessment,
IP(33), 2024, pp. 3227-3241.
IEEE DOI Code:
WWW Link.
2405
Feature extraction, Distortion, Nickel, Image quality,
Quality assessment, Semantics, Task analysis,
distribution deviation
BibRef
Wang, S.Q.[Shi-Qi],
Gu, K.[Ke],
Zeng, K.[Kai],
Wang, Z.[Zhou],
Lin, W.S.[Wei-Si],
Perceptual Screen Content Image Quality Assessment and Compression,
ICIP15(1434-1438)
IEEE DOI
1512
Information Content
BibRef
Chen, B.L.[Bao-Liang],
Li, H.L.[Hao-Liang],
Fan, H.F.[Hong-Fei],
Wang, S.Q.[Shi-Qi],
No-Reference Screen Content Image Quality Assessment with
Unsupervised Domain Adaptation,
IP(30), 2021, pp. 5463-5476.
IEEE DOI
2106
Nickel, Feature extraction, Predictive models, Image quality,
Databases, Training, Task analysis, Screen content images,
natural images
BibRef
Wang, S.Q.[Shi-Qi],
Gu, K.[Ke],
Zhang, X.F.[Xin-Feng],
Lin, W.S.[Wei-Si],
Ma, S.W.[Si-Wei],
Gao, W.[Wen],
Reduced-Reference Quality Assessment of Screen Content Images,
CirSysVideo(28), No. 1, January 2018, pp. 1-14.
IEEE DOI
1801
Feature extraction, Image edge detection, Image quality,
Prediction algorithms, Quality assessment, Uncertainty,
screen content images (SCIs)
See also Objective Quality Assessment of Screen Content Images by Uncertainty Weighting.
BibRef
Han, Z.X.[Zong-Xi],
Zhai, G.T.[Guang-Tao],
Liu, Y.T.[Yu-Tao],
Gu, K.[Ke],
Zhang, X.F.[Xin-Feng],
A Reduced-Reference Quality Assessment Scheme for Blurred Images,
VCIP16(1-4)
IEEE DOI
1701
Brain modeling
BibRef
Che, Z.H.[Zhao-Hui],
Zhai, G.T.[Guang-Tao],
Gu, K.[Ke],
Le Callet, P.[Patrick],
Reduced-reference quality metric for screen content image,
ICIP17(1852-1856)
IEEE DOI
1803
Brain modeling, Distortion, Image color analysis,
Image edge detection, Indexes, Mathematical model, Measurement, IQA,
free energy
BibRef
Gu, K.,
Wang, S.,
Zhai, G.,
Ma, S.,
Yang, X.,
Lin, W.,
Zhang, W.,
Gao, W.,
Blind Quality Assessment of Tone-Mapped Images Via Analysis of
Information, Naturalness, and Structure,
MultMed(18), No. 3, March 2016, pp. 432-443.
IEEE DOI
1603
Brightness
BibRef
Gu, K.,
Lin, W.,
Zhai, G.,
Yang, X.,
Zhang, W.,
Chen, C.W.,
No-Reference Quality Metric of Contrast-Distorted Images Based on
Information Maximization,
Cyber(47), No. 12, December 2017, pp. 4559-4565.
IEEE DOI
1712
Brain modeling, Entropy, Histograms, Image quality, Measurement,
Predictive models, Visualization, Contrast distortion,
saliency
BibRef
Min, X.,
Ma, K.,
Gu, K.,
Zhai, G.,
Wang, Z.,
Lin, W.,
Unified Blind Quality Assessment of Compressed Natural, Graphic, and
Screen Content Images,
IP(26), No. 11, November 2017, pp. 5462-5474.
IEEE DOI
1709
Databases, Distortion, Graphics, Image coding, Quality assessment,
Transform coding, Video coding, Natural scene image,
computer graphic image, high efficiency video coding (HEVC),
image quality assessment, screen content compression (SCC),
screen, content, image
BibRef
Gu, K.,
Zhou, J.,
Qiao, J.F.,
Zhai, G.,
Lin, W.S.[Wei-Si],
Bovik, A.C.,
No-Reference Quality Assessment of Screen Content Pictures,
IP(26), No. 8, August 2017, pp. 4005-4018.
IEEE DOI
1707
image colour analysis, natural scenes, regression analysis,
blind picture quality assessment algorithm, blind-NR model,
BibRef
Wu, J.J.[Jin-Jian],
Lin, W.S.[Wei-Si],
Fang, Y.M.[Yu-Ming],
Li, L.D.[Lei-Da],
Shi, G.M.[Guang-Ming],
Niwas S, I.[Issac],
Visual Structural Degradation Based Reduced-Reference Image Quality
Assessment,
SP:IC(47), No. 1, 2016, pp. 16-27.
Elsevier DOI
1610
Reduced-reference
See also No-Reference Document Image Quality Assessment Based on High Order Image Statistics.
See also Multiple-Level Feature-Based Measure for Retargeted Image Quality.
BibRef
Si, J.W.[Jian-Wei],
Huang, B.X.[Bao-Xiang],
Yang, H.[Huan],
Lin, W.S.[Wei-Si],
Pan, Z.K.[Zhen-Kuan],
A no-Reference Stereoscopic Image Quality Assessment Network Based on
Binocular Interaction and Fusion Mechanisms,
IP(31), 2022, pp. 3066-3080.
IEEE DOI
2205
Visualization, Feature extraction, Stereo image processing,
Image quality, Convolution,
binocular fusion
BibRef
Wang, X.Q.[Xiao-Qi],
Xiong, J.[Jian],
Lin, W.S.[Wei-Si],
Visual Interaction Perceptual Network for Blind Image Quality
Assessment,
MultMed(25), 2023, pp. 8958-8971.
IEEE DOI
2312
BibRef
Xiang, J.J.[Jian-Jun],
Dang, Y.J.[Yuan-Jie],
Chen, P.[Peng],
Liang, R.H.[Rong-Hua],
Lin, W.S.[Wei-Si],
Learning Decoupled Features With Perceptual Distillation for Blind
Image Quality Assessment,
IP(35), 2026, pp. 418-433.
IEEE DOI Code:
WWW Link.
2602
Distortion, Semantics, Image quality, Visualization,
Knowledge engineering, Representation learning,
local distortion-guided attention
BibRef
Pan, Z.Q.[Zhao-Qing],
Yuan, F.[Feng],
Lei, J.J.[Jian-Jun],
Fang, Y.M.[Yu-Ming],
Shao, X.[Xiao],
Kwong, S.[Sam],
VCRNet: Visual Compensation Restoration Network for No-Reference
Image Quality Assessment,
IP(31), 2022, pp. 1613-1627.
IEEE DOI
2202
Image restoration, Visualization, Image quality, Task analysis,
Feature extraction, Training, Distortion,
multi-level features
BibRef
Gu, K.[Ke],
Wang, S.Q.[Shi-Qi],
Yang, H.[Huan],
Lin, W.S.[Wei-Si],
Zhai, G.T.[Guang-Tao],
Yang, X.K.[Xiao-Kang],
Zhang, W.J.[Wen-Jun],
Saliency-Guided Quality Assessment of Screen Content Images,
MultMed(18), No. 6, June 2016, pp. 1098-1110.
IEEE DOI
1605
Convolution
See also Perceptual Quality Assessment of Screen Content Images.
BibRef
Tang, L.J.[Li-Juan],
Li, L.[Leida],
Gu, K.[Ke],
Sun, X.M.[Xing-Ming],
Zhang, J.Y.[Jian-Ying],
Blind Quality Index for Camera Images with Natural Scene Statistics
and Patch-Based Sharpness Assessment,
JVCIR(40, Part A), No. 1, 2016, pp. 335-344.
Elsevier DOI
1609
Image quality assessment (IQA)
See also Sparse Representation-Based Image Quality Index With Adaptive Sub-Dictionaries.
BibRef
Liu, Y.T.[Yu-Tao],
Zhai, G.T.[Guang-Tao],
Gu, K.[Ke],
Liu, X.M.[Xian-Ming],
Zhao, D.B.[De-Bin],
Gao, W.[Wen],
Reduced-Reference Image Quality Assessment in Free-Energy Principle
and Sparse Representation,
MultMed(20), No. 2, February 2018, pp. 379-391.
IEEE DOI
1801
Brain modeling, Distortion measurement, Feature extraction,
Image quality, Indexes, Visualization, Free-energy principle,
visual saliency
See also Using Free Energy Principle For Blind Image Quality Assessment.
BibRef
Wan, Z.L.[Zhao-Lin],
Gu, K.[Ke],
Zhao, D.B.[De-Bin],
Reduced Reference Stereoscopic Image Quality Assessment Using Sparse
Representation and Natural Scene Statistics,
MultMed(22), No. 8, August 2020, pp. 2024-2037.
IEEE DOI
2007
Visualization, Stereo image processing, Measurement,
Visual perception, Distortion, Image quality,
visual primitives
BibRef
Fang, Y.M.[Yu-Ming],
Yan, J.B.[Jie-Bin],
Liu, J.Y.[Jia-Ying],
Wang, S.Q.[Shi-Qi],
Li, Q.H.[Qiao-Hong],
Guo, Z.M.[Zong-Ming],
Objective Quality Assessment of Screen Content Images by Uncertainty
Weighting,
IP(26), No. 4, April 2017, pp. 2016-2027.
IEEE DOI
1704
Distortion
See also Saliency-Guided Quality Assessment of Screen Content Images.
BibRef
Zhou, Y.[Yu],
Li, L.[Leida],
Zhu, H.C.[Han-Cheng],
Liu, H.T.[Han-Tao],
Wang, S.Q.[Shi-Qi],
Zhao, Y.[Yao],
No-Reference Quality Assessment for Contrast-Distorted Images Based
on Multifaceted Statistical Representation of Structure,
JVCIR(60), 2019, pp. 158-169.
Elsevier DOI
1903
Quality assessment, No-reference, Contrast-distorted images,
Structure representation, Back propagation (BP)
BibRef
Wang, S.,
Gu, K.,
Ma, S.,
Gao, W.,
Joint Chroma Downsampling and Upsampling for Screen Content Image,
CirSysVideo(26), No. 9, September 2016, pp. 1595-1609.
IEEE DOI
1609
Color
BibRef
Ni, Z.,
Ma, L.,
Zeng, H.,
Cai, C.,
Ma, K.K.,
Gradient Direction for Screen Content Image Quality Assessment,
SPLetters(23), No. 10, October 2016, pp. 1394-1398.
IEEE DOI
1610
BibRef
And:
Screen content image quality assessment using edge model,
ICIP16(81-85)
IEEE DOI
1610
Computational modeling.
feature extraction
BibRef
Fu, Y.,
Zeng, H.,
Ma, L.,
Ni, Z.,
Zhu, J.,
Ma, K.K.,
Screen Content Image Quality Assessment Using Multi-Scale Difference
of Gaussian,
CirSysVideo(28), No. 9, September 2018, pp. 2428-2432.
IEEE DOI
1809
Image edge detection, Image quality, Quality assessment,
Distortion measurement, Numerical analysis, Nickel,
multi-scale difference of Gaussian
BibRef
Ni, Z.,
Ma, L.,
Zeng, H.,
Chen, J.,
Cai, C.,
Ma, K.K.,
ESIM: Edge Similarity for Screen Content Image Quality Assessment,
IP(26), No. 10, October 2017, pp. 4818-4831.
IEEE DOI
1708
edge detection, feature extraction, visual databases, ESIM, HVS, IQA,
SCI, SCI database, edge contrast, edge direction, edge features,
edge similarity, edge width,
full reference image quality assessment, human visual system,
BibRef
Ni, Z.K.[Zhang-Kai],
Zeng, H.Q.[Huan-Qiang],
Ma, L.[Lin],
Hou, J.H.[Jun-Hui],
Chen, J.[Jing],
Ma, K.K.[Kai-Kuang],
A Gabor Feature-Based Quality Assessment Model for the Screen Content
Images,
IP(27), No. 9, September 2018, pp. 4516-4528.
IEEE DOI
1807
Gabor filters, computational complexity, distortion,
edge detection, feature extraction, image classification,
screen content images (SCIs)
BibRef
Zeng, H.Q.[Huan-Qiang],
Huang, H.L.[Hai-Liang],
Hou, J.H.[Jun-Hui],
Cao, J.W.[Jiu-Wen],
Wang, Y.T.[Yong-Tao],
Ma, K.K.[Kai-Kuang],
Screen Content Video Quality Assessment Model Using Hybrid
Spatiotemporal Features,
IP(31), 2022, pp. 6175-6187.
IEEE DOI
2210
Feature extraction, Spatiotemporal phenomena, Visualization,
Quality assessment, Degradation, Video recording,
local video activity
BibRef
Guo, H.[Heng],
Ma, K.K.[Kai-Kuang],
Zeng, H.Q.[Huan-Qiang],
A Log-Gabor Feature-Based Quality Assessment Model for Screen Content
Images,
ICIP19(4499-4503)
IEEE DOI
1910
Image Quality Assessment, Screen Content Images, Gabor features, log-Gabor
BibRef
Ding, R.[Rui],
Zeng, H.Q.[Huan-Qiang],
Wen, H.[Hao],
Huang, H.L.[Hai-Liang],
Cheng, S.[Shan],
Hou, J.H.[Jun-Hui],
Screen content video quality assessment based on spatiotemporal
sparse feature,
JVCIR(96), 2023, pp. 103912.
Elsevier DOI
2310
Screen content video, Spatiotemporal sparse feature,
Three dimensional Difference of Gaussian, Dictionary learning
BibRef
Liu, Z.H.[Zhi-Hong],
Zeng, H.Q.[Huan-Qiang],
Chen, J.[Jing],
Ding, R.[Rui],
Shi, Y.F.[Yi-Fan],
Hou, J.H.[Jun-Hui],
A No-Reference Quality Assessment Model for Screen Content Videos via
Hierarchical Spatiotemporal Perception,
CirSysVideo(35), No. 2, February 2025, pp. 1422-1435.
IEEE DOI
2502
Feature extraction, Quality assessment, Visualization, Video recording,
Spatiotemporal phenomena, Streaming media, hierarchical perception
BibRef
Zhang, X.,
Lin, W.,
Wang, S.,
Liu, J.,
Ma, S.,
Gao, W.,
Fine-Grained Quality Assessment for Compressed Images,
IP(28), No. 3, March 2019, pp. 1163-1175.
IEEE DOI
1812
data compression, image coding, visual databases,
optimization methods, JPEG optimization methods,
fine-grained distortion levels
BibRef
Tang, L.J.[Li-Juan],
Sun, K.[Kezheng],
Liu, L.P.[Lu-Ping],
Wang, G.C.[Guang-Cheng],
Liu, Y.T.[Yu-Tao],
A Reduced-Reference Quality Assessment Metric for Super-Resolution
Reconstructed Images with Information Gain and Texture Similarity,
SP:IC(79), 2019, pp. 32-39.
Elsevier DOI
1911
Image quality assessment, Super-resolution reconstruction,
Information gain, Texture similarity
BibRef
Zhou, W.,
Yu, L.,
Zhou, Y.,
Qiu, W.,
Wu, M.W.,
Luo, T.,
Local and Global Feature Learning for Blind Quality Evaluation of
Screen Content and Natural Scene Images,
IP(27), No. 5, May 2018, pp. 2086-2095.
IEEE DOI
1804
feature extraction, image coding, image representation,
learning (artificial intelligence), linear codes, natural scenes,
natural scene images (NSIs)
BibRef
Yan, Q.S.[Qing-Sen],
Gong, D.[Dong],
Zhang, Y.N.[Yan-Ning],
Two-Stream Convolutional Networks for Blind Image Quality Assessment,
IP(28), No. 5, May 2019, pp. 2200-2211.
IEEE DOI
1903
feature extraction, image classification, image representation,
learning (artificial intelligence), neural nets,
no-reference (NR) IQA
BibRef
Chen, G.G.[Geng-Geng],
Dai, K.[Kexin],
Yang, K.Z.[Kang-Zhen],
Hu, T.[Tao],
Chen, X.Y.[Xiang-Yu],
Yang, Y.Q.[Yong-Qing],
Dong, W.[Wei],
Wu, P.[Peng],
Zhang, Y.N.[Yan-Ning],
Yan, Q.S.[Qing-Sen],
Bracketing Image Restoration and Enhancement with High-Low Frequency
Decomposition,
NTIRE24(6097-6107)
IEEE DOI
2410
Degradation, Feature extraction, Image restoration,
Image enhancement
BibRef
Zhang, Y.[Yi],
Chandler, D.M.[Damon M.],
Mou, X.Q.[Xuan-Qin],
Quality Assessment of Screen Content Images via
Convolutional-Neural-Network-Based Synthetic/Natural Segmentation,
IP(27), No. 10, October 2018, pp. 5113-5128.
IEEE DOI
1808
data compression, feature extraction, image segmentation,
neural nets, screen content images,
local entropy
BibRef
Chen, J.,
Shen, L.,
Zheng, L.,
Jiang, X.,
Naturalization Module in Neural Networks for Screen Content Image
Quality Assessment,
SPLetters(25), No. 11, November 2018, pp. 1685-1689.
IEEE DOI
1811
image processing, learning (artificial intelligence),
natural scenes, neural nets, visual databases,
screen content images
BibRef
Chung, K.,
Liang, Y.,
Wang, C.,
Effective Content-Aware Chroma Reconstruction Method for Screen
Content Images,
IP(28), No. 3, March 2019, pp. 1108-1117.
IEEE DOI
1812
error compensation, image colour analysis, image enhancement,
image reconstruction, image sampling, image texture, interpolation,
screen content image (SCI)
BibRef
Zhou, W.[Wujie],
Yu, L.[Lu],
Zhou, Y.[Yang],
Qiu, W.W.[Wei-Wei],
Xiang, J.[Jian],
Zhai, Z.[Zhinian],
Blind screen content image quality measurement based on sparse feature
learning,
SIViP(13), No. 3, April 2019, pp. 525-530.
Springer DOI
1904
BibRef
Rahul, K.[Kumar],
Tiwari, A.K.[Anil Kumar],
FQI: feature-based reduced-reference image quality assessment method
for screen content images,
IET-IPR(13), No. 7, 30 May 2019, pp. 1170-1180.
DOI Link
1906
BibRef
Zheng, L.R.[Lin-Ru],
Shen, L.Q.[Li-Quan],
Chen, J.N.[Jia-Nan],
An, P.[Ping],
Luo, J.[Jun],
No-Reference Quality Assessment for Screen Content Images Based on
Hybrid Region Features Fusion,
MultMed(21), No. 8, August 2019, pp. 2057-2070.
IEEE DOI
1908
feature extraction, image fusion, image representation,
image segmentation, matrix algebra, regression analysis,
hybrid-region-based features
BibRef
Jiang, X.H.[Xu-Hao],
Shen, L.Q.[Li-Quan],
Ding, Q.[Qing],
Zheng, L.R.[Lin-Ru],
An, P.[Ping],
Screen content image quality assessment based on convolutional neural
networks,
JVCIR(67), 2020, pp. 102745.
Elsevier DOI
2004
Image quality assessment, Screen content image, No-reference,
Convolutional neural network
BibRef
Jiang, X.[Xuhao],
Shen, L.Q.[Li-Quan],
Feng, G.R.[Guo-Rui],
Yu, L.W.[Liang-Wei],
An, P.[Ping],
An optimized CNN-based quality assessment model for screen content
image,
SP:IC(94), 2021, pp. 116181.
Elsevier DOI
2104
Image quality assessment, Screen content image, No-reference,
Full-reference, Convolutional neural network, Quality pooling, Data selection
BibRef
Wu, P.[Pei],
Ding, W.X.[Wen-Xin],
You, Z.X.[Zhi-Xiang],
An, P.[Ping],
Virtual Reality Video Quality Assessment Based on 3d Convolutional
Neural Networks,
ICIP19(3187-3191)
IEEE DOI
1910
Virtual Reality (VR), panoramic video,
Video Quality Assessment (VQA), 3D Convolutional Neural Network
BibRef
Cheng, S.,
Zeng, H.,
Chen, J.,
Hou, J.,
Zhu, J.,
Ma, K.,
Screen Content Video Quality Assessment: Subjective and Objective
Study,
IP(29), 2020, pp. 8636-8651.
IEEE DOI
2009
Quality assessment, Databases, Spatiotemporal phenomena,
Video recording, Distortion, Image edge detection, Tensile stress,
spatiotemporal feature tensor
BibRef
van Damme, S.[Sam],
Torres Vega, M.[Maria],
Heyse, J.[Joris],
de Backerer, F.[Femke],
de Turck, F.[Filip],
A low-complexity psychometric curve-fitting approach for the
objective quality assessment of streamed game videos,
SP:IC(88), 2020, pp. 115954.
Elsevier DOI
2009
Game video streaming (GVS), Quality of Experience (QoE),
Predictive modelling, Objective quality assessment,
Game Video Streaming Quality Metric (GVSQM)
BibRef
Fang, Y.,
Du, R.,
Zuo, Y.,
Wen, W.,
Li, L.,
Perceptual Quality Assessment for Screen Content Images by Spatial
Continuity,
CirSysVideo(30), No. 11, November 2020, pp. 4050-4063.
IEEE DOI
2011
Feature extraction, Visualization, Quality assessment,
Image quality, Distortion measurement, Image color analysis,
first-order
BibRef
Loh, W.T.[Woei-Tan],
Bong, D.B.L.[David B. L.],
A generalized quality assessment method for natural and screen
content images,
IET-IPR(15), No. 1, 2021, pp. 166-179.
DOI Link
2106
BibRef
Huang, Z.Q.[Zi-Qing],
Liu, S.G.[Shi-Guang],
Perceptual Hashing With Visual Content Understanding for
Reduced-Reference Screen Content Image Quality Assessment,
CirSysVideo(31), No. 7, July 2021, pp. 2808-2823.
IEEE DOI
2107
Visualization, Feature extraction, Image quality, Databases,
Robustness, Image coding, Perceptual hashing,
statistical feature
BibRef
Yang, J.C.[Jia-Chen],
Bian, Z.L.[Zi-Lin],
Liu, J.C.[Jia-Cheng],
Jiang, B.[Bin],
Lu, W.[Wen],
Gao, X.B.[Xin-Bo],
Song, H.B.[Hou-Bing],
No-Reference Quality Assessment for Screen Content Images Using
Visual Edge Model and AdaBoosting Neural Network,
IP(30), 2021, pp. 6801-6814.
IEEE DOI
2108
Image edge detection, Visualization, Measurement,
Feature extraction, Quality assessment, Image quality, Dogs,
AdaBoosting back-propagation neural network
BibRef
Wang, M.H.[Miao-Hui],
Liu, X.Q.[Xue-Qin],
Xie, W.[Wuyuan],
Xu, L.[Long],
Perceptual Redundancy Estimation of Screen Images via Multi-Domain
Sensitivities,
SPLetters(28), 2021, pp. 1440-1444.
IEEE DOI
2108
Sensitivity, Image edge detection, Redundancy, Visualization,
Estimation, Distortion, Transforms, Perceptual redundancy,
orientation sensitivity
BibRef
Yang, J.C.[Jia-Chen],
Bian, Z.[Zilin],
Zhao, Y.[Yang],
Lu, W.[Wen],
Gao, X.B.[Xin-Bo],
Staged-Learning: Assessing the Quality of Screen Content Images from
Distortion Information,
SPLetters(28), 2021, pp. 1480-1484.
IEEE DOI
2108
Distortion, Feature extraction, Image quality, Databases,
Visualization, Training, Convolution, Image quality assessment,
attention module
BibRef
Chang, Y.L.[Yong-Li],
Li, S.[Sumei],
Liu, A.[Anqi],
Jin, J.[Jie],
Quality assessment of screen content images based on multi-stage
dictionary learning,
JVCIR(79), 2021, pp. 103248.
Elsevier DOI
2109
Image quality assessment, Screen content images,
Sparse dictionary, Hierarchical feature extraction
BibRef
Ding, L.[Li],
Wang, P.[Ping],
Huang, H.[Hua],
Unified quality assessment of natural and screen content images via
adaptive weighting on double scales,
SP:IC(99), 2021, pp. 116446.
Elsevier DOI
2111
Image quality assessment, Screen content image,
Image structures, Structural scale, Cross-content-type image
BibRef
Min, X.K.[Xiong-Kuo],
Gu, K.[Ke],
Zhai, G.T.[Guang-Tao],
Yang, X.K.[Xiao-Kang],
Zhang, W.J.[Wen-Jun],
Le Callet, P.[Patrick],
Chen, C.W.[Chang Wen],
Screen Content Quality Assessment: Overview, Benchmark, and Beyond,
Surveys(54), No. 9, October 2021, pp. xx-yy.
DOI Link
2112
quality assessment, Screen content, quality of experience, natural scene
BibRef
Tolie, H.F.[Hamidreza Farhadi],
Faraji, M.R.[Mohammad Reza],
Screen content image quality assessment using distortion-based
directional edge and gradient similarity maps,
SP:IC(101), 2022, pp. 116562.
Elsevier DOI
2201
Screen content image, Image quality assessment,
Difference of Gaussian, Contrast change, Distortion detection
BibRef
Pan, Z.Q.[Zhao-Qing],
Yu, W.J.[Wei-Jie],
Lei, J.J.[Jian-Jun],
Ling, N.[Nam],
Kwong, S.[Sam],
TSAN: Synthesized View Quality Enhancement via Two-Stream Attention
Network for 3D-HEVC,
CirSysVideo(32), No. 1, January 2022, pp. 345-358.
IEEE DOI
2201
Image coding, Distortion,
Streaming media, Feature extraction, Encoding, Visualization,
convolutional neural networks
BibRef
Pan, Z.Q.[Zhao-Qing],
Yuan, F.[Feng],
Yu, W.J.[Wei-Jie],
Lei, J.J.[Jian-Jun],
Ling, N.[Nam],
Kwong, S.[Sam],
RDEN: Residual Distillation Enhanced Network-Guided Lightweight
Synthesized View Quality Enhancement for 3D-HEVC,
CirSysVideo(32), No. 9, September 2022, pp. 6347-6359.
IEEE DOI
2209
Feature extraction, Distortion, Data mining, Task analysis,
Visualization, Wrapping, Video recording, 3D-HEVC,
residual distillation enhanced network
BibRef
Sandic-Stankovic, D.D.[Dragana D.],
Kukolj, D.D.[Dragan D.],
Le Callet, P.[Patrick],
Quality Assessment of DIBR-Synthesized Views Based on Sparsity of
Difference of Closings and Difference of Gaussians,
IP(31), 2022, pp. 1161-1175.
IEEE DOI
2202
Feature extraction, Distortion, Measurement, Image edge detection,
Dogs, Visualization, Image representation, Difference of closings,
quality prediction
BibRef
Cheraaqee, P.[Pooryaa],
Maviz, Z.[Zahra],
Mansouri, A.[Azadeh],
Mahmoudi-Aznaveh, A.[Ahmad],
Quality Assessment of Screen Content Images in Wavelet Domain,
CirSysVideo(32), No. 2, February 2022, pp. 566-578.
IEEE DOI
2202
Image edge detection, Feature extraction, Wavelet transforms,
Measurement, Image segmentation, Kernel, Image quality,
wavelet
BibRef
Zhang, C.F.[Chao-Fan],
Huang, Z.Q.[Zi-Qing],
Liu, S.G.[Shi-Guang],
Xiao, J.[Jian],
Dual-Channel Multi-Task CNN for No-Reference Screen Content Image
Quality Assessment,
CirSysVideo(32), No. 8, August 2022, pp. 5011-5025.
IEEE DOI
2208
Feature extraction, Convolutional neural networks, Distortion,
Nickel, Multitasking, Visualization, Image quality,
histogram of oriented gradient
BibRef
Gao, R.[Rui],
Huang, Z.Q.[Zi-Qing],
Liu, S.G.[Shi-Guang],
Multi-task Deep Learning for No-reference Screen Content Image Quality
Assessment,
MMMod21(I:213-226).
Springer DOI
2106
BibRef
Zhang, K.[Kexin],
Wang, X.J.[Xue-Jin],
Chai, X.L.[Xiong-Li],
Shao, F.[Feng],
Multi-layer and Multi-scale feature aggregation for DIBR-Synthesized
image quality assessment,
JVCIR(94), 2023, pp. 103851.
Elsevier DOI
2306
Image quality assessment, DIBR-synthesized image, Distortion correction, BIQA
BibRef
Huang, Z.[Ziyin],
Chan, Y.L.[Yui-Lam],
Tsang, S.H.[Sik-Ho],
Kwong, N.W.[Ngai-Wing],
Lam, K.M.[Kin-Man],
Ling, W.K.[Wing-Kuen],
Spatio-temporal feature learning for enhancing video quality based on
screen content characteristics,
JVCIR(104), 2024, pp. 104270.
Elsevier DOI
2411
Screen content video, Quality enhancement, Deep learning
BibRef
Kwong, N.W.[Ngai-Wing],
Chan, Y.L.[Yui-Lam],
Tsang, S.H.[Sik-Ho],
Huang, Z.[Ziyin],
Lam, K.M.[Kin-Man],
Multi-Frame Spatiotemporal Feature and Hierarchical Learning Approach
for No-Reference Screen Content Video Quality Assessment,
MultMed(27), No. , 2025, pp. 7632-7647.
IEEE DOI
2510
Spatiotemporal phenomena, Feature extraction, Quality assessment,
Videos, Transformers, Training, Accuracy, Distortion, Deep learning,
temporal pyramid transformer
BibRef
Kwong, N.W.[Ngai-Wing],
Chan, Y.L.[Yui-Lam],
Tsang, S.H.[Sik-Ho],
Huang, Z.[Ziyin],
Lam, K.M.[Kin-Man],
Spatiotemporal feature learning for no-reference gaming content video
quality assessment,
JVCIR(100), 2024, pp. 104118.
Elsevier DOI
2405
Gaming content video quality assessment, Multi-task learning,
Self-supervised learning, Spatiotemporal features learning
BibRef
Jiang, S.Q.[Shi-Qi],
Ren, T.[Ting],
Fu, C.R.[Cong-Rui],
Li, S.[Shuai],
Yuan, H.[Hui],
OMR-NET: A Two-Stage Octave Multi-Scale Residual Network for Screen
Content Image Compression,
SPLetters(31), 2024, pp. 1800-1804.
IEEE DOI
2408
Image coding, Convolution, Feature extraction, Training, Decoding,
Context modeling, Standards, Screen content, image compression,
multi-scale residual block
BibRef
Song, M.K.[Meng-Ke],
Chen, C.L.Z.[Cheng-Li-Zhao],
Song, W.F.[Wen-Feng],
Fang, Y.M.[Yu-Ming],
UNI-IQA: A Unified Approach for Mutual Promotion of Natural and
Screen Content Image Quality Assessment,
CirSysVideo(35), No. 7, July 2025, pp. 6371-6385.
IEEE DOI
2507
Nickel, Training, Optical switches,
Quality assessment, Optical distortion, Multitasking, Interference,
learning to rank
BibRef
Huang, Z.[Ziyin],
Chan, Y.L.[Yui-Lam],
Kwong, N.W.[Ngai-Wing],
Tsang, S.H.[Sik-Ho],
Lam, K.M.[Kin-Man],
Ling, W.K.[Wing-Kuen],
Long Short-Term Fusion by Multi-Scale Distillation for Screen Content
Video Quality Enhancement,
CirSysVideo(35), No. 8, August 2025, pp. 7762-7777.
IEEE DOI
2508
Feature extraction, Video recording, Quality assessment, Streams,
Optical switches, Data mining, Color, Encoding, deep learning
BibRef
Chang, Y.L.[Yong-Li],
Li, S.[Sumei],
Liu, A.[Anqi],
Quality Assessment of Screen Content Images Based on Convolutional
Neural Network with Dual Pathways,
ICIP21(579-583)
IEEE DOI
2201
Integrated optics, Visualization, Sensitivity,
Image color analysis, Feature extraction, Optical imaging,
dual pathways network
BibRef
Loh, W.,
Bong, D.B.L.,
Quality Assessment for Natural and Screen Visual Contents,
ICIP19(3025-3026)
IEEE DOI
1910
screen content, natural, gradient, quality assessment.
BibRef
Wang, X.C.[Xiao-Chuan],
Wang, K.[Kai],
Yang, B.L.[Bai-Lin],
Li, F.W.B.[Frederick W.B.],
Liang, X.H.[Xiao-Hui],
Deep Blind Synthesized Image Quality Assessment with Contextual
Multi-Level Feature Pooling,
ICIP19(435-439)
IEEE DOI
1910
image quality assessment, synthesized image, feature pooling, DIBR,
deep learning
BibRef
Yue, G.,
Hou, C.,
Gu, K.,
Subjective quality assessment of animation images,
VCIP17(1-4)
IEEE DOI
1804
computer animation, distortion, image processing, natural scenes,
visual databases, AI, IQA problem, IQA research, MOS,
subjective assessment
BibRef
Wang, X.,
Cao, L.,
Zhu, Y.,
Zhang, Y.,
Jiang, J.,
Kwong, S.,
Study of subjective and objective quality assessment for screen
content images,
ICIP17(750-754)
IEEE DOI
1803
Databases, Distortion, Image quality, Measurement,
Quality assessment, Transform coding, Visualization,
Screen content image
BibRef
Heindel, A.,
Wige, E.,
Fleckenstein, F.,
Prestele, B.,
Gehlert, A.,
Kaup, A.,
A low-complexity metric for the estimation of perceived chrominance
sub-sampling errors in screen content images,
ICIP17(3225-3229)
IEEE DOI
1803
Decoding, Distortion, Encoding, Image coding, Image color analysis,
Measurement, Spatial resolution, Chrominance sub-sampling, PCSE,
screen content
BibRef
Zuo, L.X.[Ling-Xuan],
Wang, H.L.[Han-Li],
Fu, J.[Jie],
Screen content image quality assessment via convolutional neural
network,
ICIP16(2082-2086)
IEEE DOI
1610
Correlation
BibRef
Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Screen Content Coding, Compression .