12.1.4.4 Image and Sensor Fusion -- IR and Thermal with Visible

Nakamura, T.[Tetsuya],
Monitoring system employing infrared image,
US_Patent5,133,605, Jul 28, 1992
WWW Link. Visible to limit IR analysis area. BibRef 9207

Li, H.H.[Hui H.], Zhou, Y.T.[Yi-Tong],
Automatic Visual/IR Image Registration,
OptEng(35), No. 2, February 1996, pp. 391-400. BibRef 9602
Earlier:
Automatic EO/IR sensor image registration,
ICIP95(II: 161-164).
IEEE DOI 9510
BibRef
And: ICIP95(III: 240-243).
IEEE DOI 9510
BibRef

Zhou, Y.T.,
Multi-sensor image fusion,
ICIP94(I: 193-197).
IEEE DOI 9411
BibRef

Toet, A., IJspeert, J.K., Waxman, A.M., Aguilar, M.,
Fusion of Visible and Thermal Imagery Improves Situational Awareness,
Displays(18), No. 2, December 30 1997, pp. 85-95. 9802
BibRef

Agassi, E., Benyosef, N.,
Influence of Scene Topography on the Observed Correlation Between Thermal Infrared and Visible/Near-Infrared Images of Ground Terrain,
JRS(18), No. 18, December 1997, pp. 3853-3865. 9801
BibRef

Guo, L.J., Moore, J.M.,
Pixel Block Intensity Modulation: Adding Spatial Detail to TM Band-6 Thermal Imagery,
JRS(19), No. 13, September 10 1998, pp. 2477-2491. 9810
BibRef

Saraf, A.K.,
RS-1C-LISS-III and PAN data fusion: an approach to improve remote sensing based mapping techniques,
JRS(20), No. 10, July 1999, pp. 1929. BibRef 9907

Arnold, D.G.[D. Gregory], Sturtz, K.[Kirk], Velten, V.[Vince], Nandhakumar, N.,
Dominant-Subspace Invariants,
PAMI(22), No. 7, July 2000, pp. 649-662.
IEEE DOI 0008
Lie Groups. How to actually compute the invariants for some property. BibRef

Arnold, D.G.[D. Gregory], Sturtz, K.[Kirk], Velten, V.[Vince],
Lie Group Analysis in Object Recognition,
DARPA97(1173-1178). BibRef 9700

Arnold, D.G.[D. Gregory], Sturtz, K.[Kirk], Velten, V.[Vince],
Invariants of the LWIR Thermophysical Model,
CVBVS99(49).
IEEE DOI BibRef 9900
Earlier:
Quasi-Invariants of the Thermophysical Model,
DARPA98(883-892). BibRef

Segl, K., Roessner, S., Heiden, U., Kaufmann, H.,
Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data,
PandRS(58), No. 1, June 2003, pp. 99-112.
Elsevier DOI 0307
Urban features, green space. BibRef

Dousset, B., Gourmelon, F.,
Satellite multi-sensor data analysis of urban surface temperatures and landcover,
PandRS(58), No. 1, June 2003, pp. 43-54.
Elsevier DOI 0307
Energy flux of urban surface. BibRef

Liu, Z.[Zheng], Laganière, R.[Robert],
Phase congruence measurement for image similarity assessment,
PRL(28), No. 1, 1 January 2007, pp. 166-172.
Elsevier DOI 0611
Feature extraction; Phase congruence; Image comparison; Image quality evaluation BibRef

Liu, Z.[Zheng], Laganière, R.[Robert],
Context enhancement through infrared vision: a modified fusion scheme,
SIViP(1), No. 4, October 2007, pp. 293-301.
Springer DOI 0711
BibRef
Earlier:
Registration of IR and EO Video Sequences based on Frame Difference,
CRV07(459-464).
IEEE DOI 0705
BibRef

Lee, J.H., Kim, Y.S., Lee, D., Kang, D.G., Ra, J.B.,
Robust CCD and IR Image Registration Using Gradient-Based Statistical Information,
SPLetters(17), No. 4, April 2010, pp. 347-350.
IEEE DOI 1003
BibRef

Li, X., Qin, S.Y.,
Efficient fusion for infrared and visible images based on compressive sensing principle,
IET-IPR(5), No. 2, April 2011, pp. 141-147.
DOI Link 1103
BibRef

Han, J.G.[Jun-Gong], Pauwels, E.J.[Eric J.], de Zeeuw, P.[Paul],
Visible and infrared image registration in man-made environments employing hybrid visual features,
PRL(34), No. 1, 1 January 2013, pp. 42-51.
Elsevier DOI 1211
Image registration; Line detection; Geometric analysis; Local deformation BibRef

Zhang, Y.N.[Yan-Ning], Zhang, X.W.[Xiu-Wei], Maybank, S.J.[Stephen J.], Yu, R.[Rui],
An IR and visible image sequence automatic registration method based on optical flow,
MVA(24), No. 5, July 2013, pp. 947-958.
WWW Link. 1306
BibRef

Raza, S.E.A.[Shan-E-Ahmed], Sanchez, V.[Victor], Prince, G.[Gillian], Clarkson, J.P.[John P.], Rajpoot, N.M.[Nasir M.],
Registration of thermal and visible light images of diseased plants using silhouette extraction in the wavelet domain,
PR(48), No. 7, 2015, pp. 2119-2128.
Elsevier DOI 1504
Thermal and visible image registration BibRef

Xu, L.[Liang], Du, J.P.[Jun-Ping], Zhang, Z.H.[Zhen-Hong],
Infrared-visible video fusion based on motion-compensated wavelet transforms,
IET-IPR(9), No. 4, 2015, pp. 318-328.
DOI Link 1505
image fusion BibRef

Yan, X.[Xiang], Qin, H.L.[Han-Lin], Li, J.[Jia], Zhou, H.X.[Hui-Xin], Zong, J.G.[Jing-Guo],
Infrared and visible image fusion with spectral graph wavelet transform,
JOSA-A(32), No. 9, September 2015, pp. 1643-1652.
DOI Link 1509
Image processing BibRef

Bhatnagar, G.[Gaurav], Liu, Z.[Zheng],
A novel image fusion framework for night-vision navigation and surveillance,
SIViP(9), No. 1 Supp, December 2015, pp. 165-175.
WWW Link. 1601
BibRef

Li, H.G.[Hong-Guang], Ding, W.R.[Wen-Rui], Cao, X.B.[Xian-Bin], Liu, C.L.[Chun-Lei],
Image Registration and Fusion of Visible and Infrared Integrated Camera for Medium-Altitude Unmanned Aerial Vehicle Remote Sensing,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Moreno-Villamarín, D.E., Benítez-Restrepo, H.D., Bovik, A.C.,
Predicting the Quality of Fused Long Wave Infrared and Visible Light Images,
IP(26), No. 7, July 2017, pp. 3479-3491.
IEEE DOI 1706
AWGN, Databases, Distortion, Histograms, Image fusion, Sensors, Transform coding, LWIR, NSS, fusion performance, multi-resolution, image, fusion BibRef

Zhang, X.Y.[Xiao-Ye], Ma, Y.[Yong], Fan, F.[Fan], Zhang, Y.[Ying], Huang, J.[Jun],
Infrared and visible image fusion via saliency analysis and local edge-preserving multi-scale decomposition,
JOSA-A(34), No. 8, August 2017, pp. 1400-1410.
DOI Link 1708
Image processing, Digital image processing, Fusion BibRef

Guo, H.Q.[Han-Qi], Ma, Y.[Yong], Mei, X.G.[Xiao-Guang], Ma, J.Y.[Jia-Yi],
Infrared and visible image fusion based on total variation and augmented Lagrangian,
JOSA-A(34), No. 11, November 2017, pp. 1961-1968.
DOI Link 1711
Image processing, Machine vision, Fusion BibRef

Ma, J.Y.[Jia-Yi], Zhou, Y.[Yi],
Infrared and visible image fusion via gradientlet filter,
CVIU(197-198), 2020, pp. 103016.
Elsevier DOI 2008
Image fusion, Fuzzy gradient threshold function, Gradientlet filter, Saliency map, Infrared BibRef

Zhang, H.[Hao], Ma, J.Y.[Jia-Yi],
SDNet: A Versatile Squeeze-and-Decomposition Network for Real-Time Image Fusion,
IJCV(129), No. 10, October 2021, pp. 2761-2785.
Springer DOI 2110
BibRef

Hu, H.M., Wu, J., Li, B., Guo, Q., Zheng, J.,
An Adaptive Fusion Algorithm for Visible and Infrared Videos Based on Entropy and the Cumulative Distribution of Gray Levels,
MultMed(19), No. 12, December 2017, pp. 2706-2719.
IEEE DOI 1712
Distribution functions, Entropy, Filtering algorithms, Filtering theory, Transforms, Videos, visible video BibRef

Chen, Y.J.[Yan-Jia], Zhang, X.W.[Xiu-Wei], Zhang, Y.N.[Yan-Ning], Maybank, S.J.[Stephen John], Fu, Z.P.[Zhi-Peng],
Visible and infrared image registration based on region features and edginess,
MVA(29), No. 1, January 2018, pp. 113-123.
Springer DOI 1801
BibRef

Han, T.Y.[Tae Young], Kim, D.H.[Dae Ha], Lee, S.H.[Seung Hyun], Song, B.C.[Byung Cheol],
Infrared image super-resolution using auxiliary convolutional neural network and visible image under low-light conditions,
JVCIR(51), 2018, pp. 191-200.
Elsevier DOI 1802
Near-infrared and visible images, Super-resolution, Convolutional neural networks, Low-light images BibRef

Liu, X.Z.[Xiang-Zeng], Ai, Y.F.[Yun-Feng], Zhang, J.[Juli], Wang, Z.P.[Zhu-Ping],
A Novel Affine and Contrast Invariant Descriptor for Infrared and Visible Image Registration,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Yuan, X.S.[Xing-Sheng], Zhao, W.[Wei], Wang, Z.Z.[Zheng-Zhi],
Improved visual/infrared colour fusion method with double-opponency colour constancy mechanism,
IET-IPR(12), No. 9, September 2018, pp. 1560-1566.
DOI Link 1809
BibRef

Xing, C.D.[Chang-Da], Wang, Z.S.[Zhi-Sheng], Ouyang, Q.[Quan], Dong, C.[Chong],
Method based on bitonic filtering decomposition and sparse representation for fusion of infrared and visible images,
IET-IPR(12), No. 12, December 2018, pp. 2300-2310.
DOI Link 1812
BibRef

Xing, C.D.[Chang-Da], Wang, Z.S.[Zhi-Sheng], Meng, F.L.[Fan-Liang], Dong, C.[Chong],
Fusion of infrared and visible images with Gaussian smoothness and joint bilateral filtering iteration decomposition,
IET-CV(13), No. 1, February 2019, pp. 44-52.
DOI Link 1902
BibRef

Li, H., Wu, X.,
DenseFuse: A Fusion Approach to Infrared and Visible Images,
IP(28), No. 5, May 2019, pp. 2614-2623.
IEEE DOI 1903
Feature extraction, Decoding, Image coding, Image reconstruction, Training, Image fusion, Image fusion, deep learning, dense block, visible image BibRef

Jeong, S.[Somi], Kim, S.[Seungryong], Park, K.[Kihong], Sohn, K.H.[Kwang-Hoon],
Learning to Find Unpaired Cross-Spectral Correspondences,
IP(28), No. 11, November 2019, pp. 5394-5406.
IEEE DOI 1909
Feature extraction, Training, Benchmark testing, Lighting, Generative adversarial networks, Task analysis, infrared BibRef

Jung, H., Kim, Y., Jang, H., Ha, N., Sohn, K.,
Unsupervised Deep Image Fusion With Structure Tensor Representations,
IP(29), 2020, pp. 3845-3858.
IEEE DOI 2002
Image fusion, image contrast, structure tensor, convolutional neural network, and unsupervised learning BibRef

Kumar, W.K.[Wahengbam Kanan], Nongmeikapam, K.[Kishorjit], Singh, A.D.[Aheibam Dinamani],
Enhancing scene perception using a multispectral fusion of visible-near-infrared image pair,
IET-IPR(13), No. 13, November 2019, pp. 2467-2479.
DOI Link 1911
BibRef

Chen, H.[Hui], Xue, N.[Nan], Zhang, Y.P.[Yi-Peng], Lu, Q.K.[Qi-Kai], Xia, G.S.[Gui-Song],
Robust visible-infrared image matching by exploiting dominant edge orientations,
PRL(127), 2019, pp. 3-10.
Elsevier DOI 1911
Image matching, Visible and infrared images, Orientation estimation, Log-Gabor filters BibRef

Tu, Z.Z.[Zheng-Zheng], Xia, T.[Tian], Li, C.L.[Cheng-Long], Wang, X.X.[Xiao-Xiao], Ma, Y.[Yan], Tang, J.[Jin],
RGB-T Image Saliency Detection via Collaborative Graph Learning,
MultMed(22), No. 1, January 2020, pp. 160-173.
IEEE DOI 2001
Image saliency detection, RGB-thermal fusion, Collaborative graph, Joint optimization, Benchmark dataset BibRef

Jiang, B.[Bo], Jiang, X.Y.[Xing-Yue], Tang, J.[Jin], Luo, B.[Bin],
Co-Saliency Detection via a General Optimization Model and Adaptive Graph Learning,
MultMed(23), 2021, pp. 3193-3202.
IEEE DOI 2109
Optimization, Estimation, Adaptation models, Feature extraction, Predictive models, Computational modeling, Saliency detection, label propagation BibRef

He, Z.Q.[Zhou-Qin], Jiang, B.[Bo], Xiao, Y.[Yun], Ding, C.[Chris], Luo, B.[Bin],
Saliency Detection via A Graph Based Diffusion Model,
GbRPR17(3-12).
Springer DOI 1706
BibRef

Liu, Y.C.[Yao-Chen], Dong, L.L.[Li-Li], Chen, Y.[Yang], Xu, W.H.[Wen-Hai],
An Efficient Method for Infrared and Visual Images Fusion Based on Visual Attention Technique,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Li, H., Wu, X., Kittler, J.V.,
MDLatLRR: A Novel Decomposition Method for Infrared and Visible Image Fusion,
IP(29), 2020, pp. 4733-4746.
IEEE DOI 2003
Image fusion, Task analysis, Transforms, Matrix decomposition, Sparse matrices, Feature extraction, Image decomposition, visible image BibRef

Min, C.[Chaobo], Gu, Y.[Yan], Li, Y.J.[Ying-Jie], Yang, F.[Feng],
Non-rigid infrared and visible image registration by enhanced affine transformation,
PR(106), 2020, pp. 107377.
Elsevier DOI 2006
Registration, Non-rigid transformation, Infrared image, Image fusion BibRef

Min, C.[Chaobo], Gu, Y.[Yan], Li, Y.J.[Ying-Jie], Yang, F.[Feng],
Adaptive enhanced affine transformation for non-rigid registration of visible and infrared images,
IET-IPR(15), No. 5, 2021, pp. 1144-1156.
DOI Link 2106
BibRef

Sharma, A.M.[Apoorav M.], Dogra, A.[Ayush], Goyal, B.[Bhawna], Vig, R.[Renu], Agrawal, S.I.[Sun-Il],
From pyramids to state-of-the-art: a study and comprehensive comparison of visible-infrared image fusion techniques,
IET-IPR(14), No. 9, 20 July 2020, pp. 1671-1689.
DOI Link 2007
BibRef

Shen, D.H.[Dong-Hao], Zareapoor, M.[Masoumeh], Yang, J.[Jie],
Infrared and visible image fusion via global variable consensus,
IVC(104), 2020, pp. 104037.
Elsevier DOI 2012
Image fusion, Infrared, Consensus, Total variation, ADMM BibRef

Li, Z.[Zhuo], Hu, H.M.[Hai-Miao], Zhang, W.[Wei], Pu, S.L.[Shi-Liang], Li, B.[Bo],
Spectrum Characteristics Preserved Visible and Near-Infrared Image Fusion Algorithm,
MultMed(23), 2021, pp. 306-319.
IEEE DOI 2012
Image color analysis, Scattering, Lighting, Degradation, Distortion, Image fusion, Indexes, Image Fusion, near infrared, image enhancement BibRef

Li, L.[Lei], Xia, Z.Q.[Zhao-Qiang], Han, H.J.[Hui-Jian], He, G.Q.[Gui-Qing], Roli, F.[Fabio], Feng, X.Y.[Xiao-Yi],
Infrared and visible image fusion using a shallow CNN and structural similarity constraint,
IET-IPR(14), No. 14, December 2020, pp. 3562-3571.
DOI Link 2012
BibRef

Selvaraj, A.[Arivazhagan], Ganesan, P.[Prema],
Infrared and visible image fusion using multi-scale NSCT and rolling-guidance filter,
IET-IPR(14), No. 16, 19 December 2020, pp. 4210-4219.
DOI Link 2103
BibRef

Duan, C.W.[Chao-Wei], Xing, C.D.[Chang-Da], Lu, S.S.[Shan-Shan], Wang, Z.S.[Zhi-Sheng],
Two-scale fusion method of infrared and visible images via parallel saliency features,
IET-IPR(14), No. 16, 19 December 2020, pp. 4412-4423.
DOI Link 2103
BibRef

Li, H.F.[Hua-Feng], Cen, Y.L.[Yue-Liang], Liu, Y.[Yu], Chen, X.[Xun], Yu, Z.T.[Zheng-Tao],
Different Input Resolutions and Arbitrary Output Resolution: A Meta Learning-Based Deep Framework for Infrared and Visible Image Fusion,
IP(30), 2021, pp. 4070-4083.
IEEE DOI 2104
Image fusion, Feature extraction, Superresolution, Spatial resolution, Frequency modulation, Sensor fusion, super-resolution BibRef

Li, J.[Jing], Huo, H.T.[Hong-Tao], Li, C.[Chang], Wang, R.H.[Ren-Hua], Feng, Q.[Qi],
AttentionFGAN: Infrared and Visible Image Fusion Using Attention-Based Generative Adversarial Networks,
MultMed(23), 2021, pp. 1383-1396.
IEEE DOI 2105
Image fusion, Generative adversarial networks, Feature extraction, Transforms, Generators, Fuses, infrared and visible image fusion BibRef

Wang, L.[Lan], Gao, C.Q.[Chen-Qiang], Zhao, Y.[Yue], Song, T.C.[Tie-Cheng], Feng, Q.[Qi],
Infrared and Visible Image Registration Using Transformer Adversarial Network,
ICIP18(1248-1252)
IEEE DOI 1809
Image registration, Task analysis, Training, Feature extraction, Imaging, Transforms, Image Registration, Infrared Image BibRef

Budhiraja, S.[Sumit], Rummy, I.[Iftisam], Agrawal, S.I.[Sun-Il], Sohi, B.S.[Balwinder Singh],
Infrared and Visible Image Fusion Based on Sparse Representation and Spatial Frequency in DTCWT Domain,
IJIG(21), No. 2 2021, pp. 2150017.
DOI Link 2105
BibRef

Herrera-Arellano, M.[María], Peregrina-Barreto, H.[Hayde], Terol-Villalobos, I.[Iván],
Visible-NIR Image Fusion Based on Top-Hat Transform,
IP(30), 2021, pp. 4962-4972.
IEEE DOI 2106
Image color analysis, Image fusion, Transforms, Image edge detection, Entropy, Color, Morphology, V-NIR image fusion, mathematical morphology BibRef

Xu, Z.[Zhao], Liu, G.[Gang], Xiao, G.[Gang], Tang, L.[Lili], Li, Y.H.[Yan-Hui],
JCa2Co: A joint cascade convolution coding network based on fuzzy regional characteristics for infrared and visible image fusion,
IET-CV(15), No. 7, 2021, pp. 487-500.
DOI Link 2109
BibRef

Tan, M.J.[Min-Jie], Gao, S.B.[Shao-Bing], Xu, W.Z.[Wen-Zheng], Han, S.C.[Song-Chen],
Visible-Infrared Image Fusion Based on Early Visual Information Processing Mechanisms,
CirSysVideo(31), No. 11, November 2021, pp. 4357-4369.
IEEE DOI 2112
Image color analysis, Visualization, Adaptation models, Radio frequency, Task analysis, Fuses, Brain modeling, Image fusion, visible and infrared image processing BibRef

Yang, Y.[Yong], Liu, J.X.[Jia-Xiang], Huang, S.Y.[Shu-Ying], Wan, W.G.[Wei-Guo], Wen, W.Y.[Wen-Ying], Guan, J.W.[Ju-Wei],
Infrared and Visible Image Fusion via Texture Conditional Generative Adversarial Network,
CirSysVideo(31), No. 12, December 2021, pp. 4771-4783.
IEEE DOI 2112
Image fusion, Generators, Information filters, Generative adversarial networks, Feature extraction, multiple decision maps BibRef

Qi, B.[Biao], Jin, L.X.[Long-Xu], Li, G.[Guoning], Zhang, Y.[Yu], Li, Q.[Qiang], Bi, G.L.[Guo-Ling], Wang, W.H.[Wen-Hua],
Infrared and Visible Image Fusion Based on Co-Occurrence Analysis Shearlet Transform,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Bhutto, J.A.[Jameel Ahmed], Tian, L.[Lianfang], Du, Q.L.[Qi-Liang], Sun, Z.Z.[Zheng-Zheng], Yu, L.[Lubin], Soomro, T.A.[Toufique Ahmed],
An Improved Infrared and Visible Image Fusion Using an Adaptive Contrast Enhancement Method and Deep Learning Network with Transfer Learning,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Zhao, Z.X.[Zi-Xiang], Xu, S.[Shuang], Zhang, J.S.[Jiang-She], Liang, C.Y.[Cheng-Yang], Zhang, C.X.[Chun-Xia], Liu, J.[Junmin],
Efficient and Model-Based Infrared and Visible Image Fusion via Algorithm Unrolling,
CirSysVideo(32), No. 3, March 2022, pp. 1186-1196.
IEEE DOI 2203
Optimization, Image fusion, Feature extraction, Task analysis, Kernel, Decoding, Neural networks, Image fusion, model-based network structure BibRef

Nie, R.[Rencan], Ma, C.Z.[Chao-Zhen], Cao, J.[Jinde], Ding, H.W.[Hong-Wei], Zhou, D.M.[Dong-Ming],
A Total Variation With Joint Norms For Infrared and Visible Image Fusion,
MultMed(24), 2022, pp. 1460-1472.
IEEE DOI 2204
Image fusion, Estimation, Degradation, Task analysis, Fuses, Biomedical imaging, TV, Infrared and visible image fusion, weight estimation BibRef

Chen, J.F.[Jin-Fen], Cheng, B.[Bo], Zhang, X.P.[Xiao-Ping], Long, T.F.[Teng-Fei], Chen, B.[Bo], Wang, G.Z.[Gui-Zhou], Zhang, D.G.[De-Gang],
A TIR-Visible Automatic Registration and Geometric Correction Method for SDGSAT-1 Thermal Infrared Image Based on Modified RIFT,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Wang, H.M.[Hong-Mei], An, W.B.[Wen-Bo], Li, L.[Lin], Li, C.K.[Chen-Kai], Zhou, D.M.[Da-Ming],
Infrared and visible image fusion based on multi-channel convolutional neural network,
IET-IPR(16), No. 6, 2022, pp. 1575-1584.
DOI Link 2204
BibRef

Xu, H.[Han], Gong, M.[Meiqi], Tian, X.[Xin], Huang, J.[Jun], Ma, J.Y.[Jia-Yi],
CUFD: An encoder-decoder network for visible and infrared image fusion based on common and unique feature decomposition,
CVIU(218), 2022, pp. 103407.
Elsevier DOI 2205
Image fusion, Infrared, Visible, Feature map, Encoder-decoder BibRef

Ruan, Z.Q.[Zhi-Qiang], Wan, J.[Jie], Xiao, G.[Guobao], Tang, Z.M.[Zhi-Min], Ma, J.Y.[Jia-Yi],
Semantic attention-based heterogeneous feature aggregation network for image fusion,
PR(155), 2024, pp. 110728.
Elsevier DOI 2408
Image fusion, High-level vision tasks, Attention mechanism, Semantic prior BibRef

Qiu, X.F.[Xian-Fei], Zhao, H.J.[Hui-Jie], Jia, G.R.[Guo-Rui], Li, J.Y.[Ji-Yuan],
Atmosphere and Terrain Coupling Simulation Framework for High-Resolution Visible-Thermal Spectral Imaging over Heterogeneous Land Surface,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Zhou, W.[Wujie], Lin, X.Y.[Xin-Yang], Lei, J.S.[Jing-Sheng], Yu, L.[Lu], Hwang, J.N.[Jenq-Neng],
MFFENet: Multiscale Feature Fusion and Enhancement Network For RGB-Thermal Urban Road Scene Parsing,
MultMed(24), 2022, pp. 2526-2538.
IEEE DOI 2205
Autonomous driving, urban road scene, semantic segmentation, thermal image, multi-task supervision BibRef

Özer, S.[Sedat], Ege, M.[Mert], Özkanoglu, M.A.[Mehmet Akif],
SiameseFuse: A computationally efficient and a not-so-deep network to fuse visible and infrared images,
PR(129), 2022, pp. 108712.
Elsevier DOI 2206
Multi-temporal fusion, Efficient learning, Multi-modal fusion BibRef

Wang, Z.S.[Zhi-She], Wang, J.Y.[Jun-Yao], Wu, Y.Y.[Yuan-Yuan], Xu, J.W.[Jia-Wei], Zhang, X.Q.[Xiao-Qin],
UNFusion: A Unified Multi-Scale Densely Connected Network for Infrared and Visible Image Fusion,
CirSysVideo(32), No. 6, June 2022, pp. 3360-3374.
IEEE DOI 2206
Feature extraction, Image fusion, Image reconstruction, Task analysis, Decoding, Training, Learning systems, Image fusion, visible image BibRef

Zhang, Z.H.[Zi-Han], Wu, X.J.[Xiao-Jun], Xu, T.Y.[Tian-Yang],
FPNFuse: A lightweight feature pyramid network for infrared and visible image fusion,
IET-IPR(16), No. 9, 2022, pp. 2308-2320.
DOI Link 2206
BibRef

Cheng, C.[Chen], Sun, C.[Cheng], Sun, Y.Q.[Yong-Qi], Zhu, J.[Jiahui],
StyleFuse: An unsupervised network based on style loss function for infrared and visible image fusion,
SP:IC(106), 2022, pp. 116722.
Elsevier DOI 2206
Image fusion, Infrared image, Visible image, Style loss, Style transfer BibRef

Gao, X.Y.[Xu-Yang], Shi, Y.B.[Yi-Bing], Zhu, Q.[Qi], Fu, Q.[Qiang], Wu, Y.Z.[Yue-Zhou],
Infrared and Visible Image Fusion with Deep Neural Network in Enhanced Flight Vision System,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Jian, L.H.[Li-Hua], Rayhana, R.[Rakiba], Ma, L.[Ling], Wu, S.W.[Shao-Wu], Liu, Z.[Zheng], Jiang, H.Q.[Hui-Qin],
Infrared and Visible Image Fusion Based on Deep Decomposition Network and Saliency Analysis,
MultMed(24), 2022, pp. 3314-3326.
IEEE DOI 2207
Feature extraction, Image fusion, Task analysis, Fuses, Visualization, Image edge detection, Data mining, visual saliency mechanism BibRef

Liu, X.Z.[Xiang-Zeng], Gao, H.J.[Hao-Jie], Miao, Q.G.[Qi-Guang], Xi, Y.[Yue], Ai, Y.F.[Yun-Feng], Gao, D.G.[Ding-Guo],
MFST: Multi-Modal Feature Self-Adaptive Transformer for Infrared and Visible Image Fusion,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Liu, X.Z.[Xiang-Zeng], Wang, Z.[Ziyao], Gao, H.J.[Hao-Jie], Li, X.[Xiang], Wang, L.[Lei], Miao, Q.G.[Qi-Guang],
HATF: Multi-Modal Feature Learning for Infrared and Visible Image Fusion via Hybrid Attention Transformer,
RS(16), No. 5, 2024, pp. 803.
DOI Link 2403
BibRef

Meng, L.X.[Ling-Xuan], Zhou, J.[Ji], Liu, S.M.[Shao-Min], Wang, Z.W.[Zi-Wei], Zhang, X.D.[Xiao-Dong], Ding, L.R.[Li-Rong], Shen, L.[Li], Wang, S.F.[Shao-Fei],
A robust registration method for UAV thermal infrared and visible images taken by dual-cameras,
PandRS(192), 2022, pp. 189-214.
Elsevier DOI 2209
Template matching, Pyramid similarity maps, Multilevel local max-pooling, Homography estimation, UAV remote sensing BibRef

Wu, Y.[Yubin], Cheng, L.L.[Liang-Lun], Wang, T.[Tao], Wu, H.[Heng],
Infrared and visible light dual-camera super-resolution imaging with texture transfer network,
SP:IC(108), 2022, pp. 116825.
Elsevier DOI 2209
Infrared image, Super-resolution, Texture transfer, Cross-scale residual BibRef

Xu, M.L.[Mei-Long], Tang, L.F.[Lin-Feng], Zhang, H.[Hao], Ma, J.Y.[Jia-Yi],
Infrared and visible image fusion via parallel scene and texture learning,
PR(132), 2022, pp. 108929.
Elsevier DOI 2209
Image fusion, Infrared, Scene and texture learning, Recurrent neural network BibRef

Yin, H.T.[Hai-Tao], Xiao, J.[Jinghu],
Laplacian Pyramid Generative Adversarial Network for Infrared and Visible Image Fusion,
SPLetters(29), 2022, pp. 1988-1992.
IEEE DOI 2210
Feature extraction, Laplace equations, Image fusion, Generative adversarial networks, Generators, Training, Decoding, attention module BibRef

Patrucco, G.[Giacomo], Gómez, A.[Antonio], Adineh, A.[Ali], Rahrig, M.[Max], Lerma, J.L.[José Luis],
3D Data Fusion for Historical Analyses of Heritage Buildings Using Thermal Images: The Palacio de Colomina as a Case Study,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Patrucco, G., Cortese, G., Tonolo, F.G.[F. Giulio], Spanò, A.,
Thermal and Optical Data Fusion Supporting Built Heritage Analyses,
ISPRS20(B3:619-626).
DOI Link 2012
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Qi, L.T.[Lin-Tong], Hu, Z.Y.[Zhuo-Yue], Zhou, X.X.[Xiao-Xuan], Ni, X.Y.[Xin-Yue], Chen, F.S.[Fan-Sheng],
Multi-Sensor Fusion of SDGSAT-1 Thermal Infrared and Multispectral Images,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Pu, Q.[Qin], Chehri, A.[Abdellah], Jeon, G.G.[Gwang-Gil], Zhang, L.[Lei], Yang, X.M.[Xiao-Min],
DCFusion: Dual-Headed Fusion Strategy and Contextual Information Awareness for Infrared and Visible Remote Sensing Image,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Nie, C.[Cairen], Zhou, D.M.[Dong-Ming], Nie, R.[Rencan],
EDAfuse: A encoder-decoder with atrous spatial pyramid network for infrared and visible image fusion,
IET-IPR(17), No. 1, 2023, pp. 132-143.
DOI Link 2301
BibRef

Liu, Y.X.[Yu-Xiang], Liu, Y.[Yu], Yan, S.[Shen], Chen, C.[Chen], Zhong, J.[Jikun], Peng, Y.[Yang], Zhang, M.[Maojun],
A Multi-View Thermal-Visible Image Dataset for Cross-Spectral Matching,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Kim, J.H.[Jun-Hyung], Hwang, Y.[Youngbae],
Infrared and visible image fusion using a guiding network to leverage perceptual similarity,
CVIU(227), 2023, pp. 103598.
Elsevier DOI 2301
Image fusion, Perceptual loss, Downstream tasks, Infrared image BibRef

Zhou, L.[Lin], Chen, Z.Z.[Zhen-Zhong],
Illumination-aware window transformer for RGBT modality fusion,
JVCIR(90), 2023, pp. 103725.
Elsevier DOI 2301
Multispectral image, Multi-modal learning, Transformers BibRef

Gao, Y.[Yuan], Ma, S.W.[Shi-Wei], Liu, J.J.[Jing-Jing],
DCDR-GAN: A Densely Connected Disentangled Representation Generative Adversarial Network for Infrared and Visible Image Fusion,
CirSysVideo(33), No. 2, February 2023, pp. 549-561.
IEEE DOI 2302
Image fusion, Generative adversarial networks, Decoding, Feature extraction, Generators, Image reconstruction, Encoding, visible image fusion BibRef

Alparone, L.[Luciano], Garzelli, A.[Andrea], Zoppetti, C.[Claudia],
Fusion of VNIR Optical and C-Band Polarimetric SAR Satellite Data for Accurate Detection of Temporal Changes in Vegetated Areas,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Li, S.S.[Sheng-Shi], Zou, Y.H.[Yong-Hua], Wang, G.J.[Guan-Jun], Lin, C.[Cong],
Infrared and Visible Image Fusion Method Based on a Principal Component Analysis Network and Image Pyramid,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Tang, W.[Wei], He, F.[Fazhi], Liu, Y.[Yu],
TCCFusion: An infrared and visible image fusion method based on transformer and cross correlation,
PR(137), 2023, pp. 109295.
Elsevier DOI 2302
Image fusion, Transformer, Deep learning, Infrared image, Cross correlation BibRef

Zhou, H.B.[Hua-Bing], Wu, W.[Wei], Zhang, Y.[Yanduo], Ma, J.Y.[Jia-Yi], Ling, H.B.[Hai-Bin],
Semantic-Supervised Infrared and Visible Image Fusion Via a Dual-Discriminator Generative Adversarial Network,
MultMed(25), 2023, pp. 635-648.
IEEE DOI 2302
Image fusion, Semantics, Feature extraction, Generators, Transforms, Generative adversarial networks, Games, Image fusion, dual-discriminator BibRef

Zhao, L.J.[Liang-Jun], Yang, H.[Hao], Dong, L.[Linlu], Zheng, L.P.[Li-Ping], Asiya, M.[Manlike], Zheng, F.L.[Feng-Ling],
MMFuse: A multi-scale infrared and visible images fusion algorithm based on morphological reconstruction and membership filtering,
IET-IPR(17), No. 4, 2023, pp. 1126-1148.
DOI Link 2303
Image fusion, Multi-scale transformation, Fuzzy c-means clustering(FCM), Morphological reconstruction (MR) BibRef

Luo, X.Q.[Xiao-Qing], Jiang, Y.T.[Yu-Ting], Wang, A.[Anqi], Wang, J.[Juan], Zhang, Z.[Zhancheng], Wu, X.J.[Xiao-Jun],
Infrared and visible image fusion based on Multi-State contextual hidden Markov Model,
PR(138), 2023, pp. 109431.
Elsevier DOI 2303
Image fusion, non-subsampled Shearlet transform, contextual hidden Markov model, multi-state, soft context variable BibRef

Chang, Z.H.[Zhi-Hao], Feng, Z.X.[Zhi-Xi], Yang, S.Y.[Shu-Yuan], Gao, Q.W.[Quan-Wei],
AFT: Adaptive Fusion Transformer for Visible and Infrared Images,
IP(32), 2023, pp. 2077-2092.
IEEE DOI 2304
Transformers, Feature extraction, Decoding, Convolution, Visualization, Image fusion, Fuses, Multi-modality images, multi-head self-fusion BibRef

Fang, A.Q.[Ai-Qing], Wu, J.S.[Jun-Sheng], Li, Y.[Ying], Qiao, R.M.[Rui-Min],
Infrared and visible image fusion via mutual information maximization,
CVIU(231), 2023, pp. 103683.
Elsevier DOI 2305
Image fusion, Neural network, Mutual information, Deep learning BibRef

Wu, Y.H.[Yu-Hui], Liu, Z.[Zhu], Liu, J.Y.[Jin-Yuan], Fan, X.[Xin], Liu, R.S.[Ri-Sheng],
Breaking Free From Fusion Rule: A Fully Semantic-Driven Infrared and Visible Image Fusion,
SPLetters(30), 2023, pp. 418-422.
IEEE DOI 2305
Semantics, Training, Task analysis, Feature extraction, Image fusion, Fuses, Image fusion, semantic-driven training strategy BibRef

Ji, C.M.[Chuan-Ming], Zhou, W.[Wujie], Lei, J.S.[Jing-Sheng], Ye, L.[Lv],
Infrared and Visible Image Fusion via Multiscale Receptive Field Amplification Fusion Network,
SPLetters(30), 2023, pp. 493-497.
IEEE DOI 2305
Feature extraction, Image fusion, Convolution, Transformers, Signal processing algorithms, Image edge detection, Image fusion, deep learning BibRef

Zhou, X.L.[Xiao-Ling], Jiang, Z.[Zetao], Okuwobi, I.P.[Idowu Paul],
Retinex-MPCNN: A Retinex and Modified Pulse coupled Neural Network based method for low-illumination visible and infrared image fusion,
SP:IC(115), 2023, pp. 116956.
Elsevier DOI 2306
MPCNN, Parameters setting, Retinex theory, Low illumination enhancement, Weighted image fusion BibRef

Li, L.L.[Liang-Liang], Lv, M.[Ming], Jia, Z.H.[Zhen-Hong], Jin, Q.X.[Qing-Xin], Liu, M.Q.[Min-Qin], Chen, L.[Liangfu], Ma, H.B.[Hong-Bing],
An Effective Infrared and Visible Image Fusion Approach via Rolling Guidance Filtering and Gradient Saliency Map,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Qi, B.[Biao], Bai, X.T.[Xiao-Tian], Wu, W.[Wei], Zhang, Y.[Yu], Lv, H.[Hengyi], Li, G.[Guoning],
A Novel Saliency-Based Decomposition Strategy for Infrared and Visible Image Fusion,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Zhao, L.X.[Li-Xing], Jiao, J.J.[Jing-Jie], Yang, L.[Lan], Pan, W.H.[Wen-Hao], Zeng, F.[Fanjun], Li, X.Y.[Xiao-Yan], Chen, F.S.[Fan-Sheng],
A CNN-Based Layer-Adaptive GCPs Extraction Method for TIR Remote Sensing Images,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
Thermal Infrared Images. BibRef

Kolf, J.N.[Jan Niklas], Elliesen, J.[Jurek], Boutros, F.[Fadi], Proença, H.[Hugo], Damer, N.[Naser],
SyPer: Synthetic periocular data for quantized light-weight recognition in the NIR and visible domains,
IVC(135), 2023, pp. 104692.
Elsevier DOI 2306
Deep learning, Quantization, Synthetic data, Biometrics, Periocular BibRef

Li, X.[Xilai], Li, X.S.[Xiao-Song], Liu, W.Y.[Wu-Yang],
CBFM: Contrast Balance Infrared and Visible Image Fusion Based on Contrast-Preserving Guided Filter,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
BibRef

Ying, J.C.[Jia-Cheng], Tong, C.[Can], Sheng, Z.[Zehua], Yao, B.[Bowen], Cao, S.Y.[Si-Yuan], Yu, H.[Heng], Shen, H.L.[Hui-Liang],
Region-aware RGB and near-infrared image fusion,
PR(142), 2023, pp. 109717.
Elsevier DOI 2307
Image fusion, RGB and near-infrared, overexposed sky recovery, vegetation enhancement, gradient-domain optimization BibRef

Tang, W.[Wei], He, F.[Fazhi], Liu, Y.[Yu], Duan, Y.S.[Yan-Song], Si, T.Z.[Tong-Zhen],
DATFuse: Infrared and Visible Image Fusion via Dual Attention Transformer,
CirSysVideo(33), No. 7, July 2023, pp. 3159-3172.
IEEE DOI 2307
Transformers, Image fusion, Feature extraction, Task analysis, Transmission line measurements, Decoding, Computational modeling, residual learning BibRef

Tang, W.[Wei], He, F.[Fazhi], Liu, Y.[Yu],
ITFuse: An interactive transformer for infrared and visible image fusion,
PR(156), 2024, pp. 110822.
Elsevier DOI Code:
WWW Link. 2408
Image fusion, Transformer, Interactive network, Infrared image, Deep learning BibRef

Tang, W.[Wei], He, F.[Fazhi], Liu, Y.[Yu],
YDTR: Infrared and Visible Image Fusion via Y-Shape Dynamic Transformer,
MultMed(25), 2023, pp. 5413-5428.
IEEE DOI 2311
BibRef

Wang, X.Y.[Xing-Yi], Luo, Y.H.[Yin-Hui], Fu, Q.[Qiang], Rui, Y.[Yun], Shu, C.[Chang], Wu, Y.Z.[Yue-Zhou], He, Z.[Zhige], He, Y.Q.[Yuan-Qing],
Infrared and Visible Image Homography Estimation Based on Feature Correlation Transformers for Enhanced 6G Space-Air-Ground Integrated Network Perception,
RS(15), No. 14, 2023, pp. 3535.
DOI Link 2307
BibRef

Wang, Z.S.[Zhi-She], Shao, W.Y.[Wen-Yu], Chen, Y.L.[Yan-Lin], Xu, J.W.[Jia-Wei], Zhang, L.[Lei],
A Cross-Scale Iterative Attentional Adversarial Fusion Network for Infrared and Visible Images,
CirSysVideo(33), No. 8, August 2023, pp. 3677-3688.
IEEE DOI 2308
Feature extraction, Iterative methods, Generators, Task analysis, Image reconstruction, Iterative decoding, Image fusion, adversarial learning BibRef

Wang, Z.S.[Zhi-She], Shao, W.Y.[Wen-Yu], Chen, Y.L.[Yan-Lin], Xu, J.W.[Jia-Wei], Zhang, X.Q.[Xiao-Qin],
Infrared and Visible Image Fusion via Interactive Compensatory Attention Adversarial Learning,
MultMed(25), 2023, pp. 7800-7813.
IEEE DOI 2312
BibRef

Yi, S.[Shi], Chen, M.T.[Meng-Ting], Liu, X.[Xi], Li, J.J.[Jun-Jie], Chen, L.[Ling],
HAFFseg: RGB-Thermal semantic segmentation network with hybrid adaptive feature fusion strategy,
SP:IC(117), 2023, pp. 117027.
Elsevier DOI 2308
RGB-Thermal semantic segmentation, Frequency domain feature enhanced module, Full-scale fusion connection decoder BibRef

Zhang, C.F.[Cheng-Fang], Li, H.Y.[Hao-Yue], Feng, Z.L.[Zi-Liang], He, S.[Sidi],
Joint coupled dictionaries-based visible-infrared image fusion method via texture preservation structure in sparse domain,
CVIU(235), 2023, pp. 103781.
Elsevier DOI 2310
Visible and infrared image fusion, Coupled dictionary learning, Joint sparse coding, Texture preserving BibRef

Ahn, S.[Seongyong], Shim, I.[Inwook], Min, J.H.[Ji-Hong], Yoon, K.J.[Kuk-Jin],
EasyFuse: Easy-to-learn visible and infrared image fusion framework based on unpaired set,
PRL(174), 2023, pp. 99-105.
Elsevier DOI 2310
Image fusion, Visible and infrared image, Multi-modal image, Unsupervised learning BibRef

Yao, J.X.[Jia-Xin], Zhao, Y.Q.[Yong-Qiang], Bu, Y.Y.[Yuan-Yang], Kong, S.G.[Seong G.], Chan, J.C.W.[Jonathan Cheung-Wai],
Laplacian Pyramid Fusion Network With Hierarchical Guidance for Infrared and Visible Image Fusion,
CirSysVideo(33), No. 9, September 2023, pp. 4630-4644.
IEEE DOI 2310
BibRef

Wang, H.Z.[Hao-Zhe], Shu, C.[Chang], Li, X.F.[Xiao-Feng],
Enlighten Fusion Multiscale Network for Infrared and Visible Image Fusion in Dark Environments,
SPLetters(30), 2023, pp. 1167-1171.
IEEE DOI 2310
BibRef

Yue, J.[Jun], Fang, L.Y.[Le-Yuan], Xia, S.B.[Shao-Bo], Deng, Y.[Yue], Ma, J.Y.[Jia-Yi],
Dif-Fusion: Toward High Color Fidelity in Infrared and Visible Image Fusion With Diffusion Models,
IP(32), 2023, pp. 5705-5720.
IEEE DOI Code:
WWW Link. 2311
BibRef

Kuppala, K.[Kavitha], Banda, S.[Sandhya], Imambi, S.S.[S. Sagar],
Unsupervised image transformation for long wave infrared and visual image matching using two channel convolutional autoencoder network,
IJCVR(14), No. 1, 2024, pp. 63-83.
DOI Link 2312
BibRef

Wan, R.J.[Ren-Jie], Shi, B.X.[Bo-Xin], Yang, W.H.[Wen-Han], Wen, B.[Bihan], Duan, L.Y.[Ling-Yu], Kot, A.C.[Alex C.],
Purifying Low-Light Images via Near-Infrared Enlightened Image,
MultMed(25), 2023, pp. 8006-8019.
IEEE DOI 2312
BibRef

Tian, S.L.[Shu-Lin], Wang, Y.F.[Yu-Fei], Wan, R.J.[Ren-Jie], Yang, W.H.[Wen-Han], Kot, A.C.[Alex C.], Wen, B.[Bihan],
Enhancing Low-Light Images Using Infrared Encoded Images,
ICIP23(465-469)
IEEE DOI Code:
WWW Link. 2312
BibRef

Li, J.Q.[Jia-Qi], Bi, G.[Guoling], Wang, X.Z.[Xiao-Zhen], Nie, T.[Ting], Huang, L.[Liang],
Radiation-Variation Insensitive Coarse-to-Fine Image Registration for Infrared and Visible Remote Sensing Based on Zero-Shot Learning,
RS(16), No. 2, 2024, pp. 214.
DOI Link 2402
BibRef

Luo, X.Q.[Xiao-Qing], Wang, J.[Juan], Zhang, Z.C.[Zhan-Cheng], Wu, X.J.[Xiao-Jun],
A full-scale hierarchical encoder-decoder network with cascading edge-prior for infrared and visible image fusion,
PR(148), 2024, pp. 110192.
Elsevier DOI Code:
WWW Link. 2402
Full-scale, Long-range, Progressive semantic, Edge-prior, Encoder-decoder, Infrared and visible image fusion BibRef

Park, S.[Seonghyun], Vien, A.G.[An Gia], Lee, C.[Chul],
Cross-Modal Transformers for Infrared and Visible Image Fusion,
CirSysVideo(34), No. 2, February 2024, pp. 770-785.
IEEE DOI 2402
BibRef
Earlier:
Infrared and Visible Image Fusion Using Bimodal Transformers,
ICIP22(1741-1745)
IEEE DOI 2211
Feature extraction, Transformers, Image fusion, Convolution, Task analysis, Data mining, Image fusion, transformer, visible image. Frequency-domain analysis, Merging, Image reconstruction, multiscale network BibRef

Yang, S.H.[Shi-Hao], Sun, M.[Min], Lou, X.[Xiayin], Yang, H.[Hanjun], Liu, D.[Dong],
Nighttime Thermal Infrared Image Translation Integrating Visible Images,
RS(16), No. 4, 2024, pp. 666.
DOI Link 2402
BibRef

Li, X.L.[Xiao-Ling], Li, Y.F.[Yan-Feng], Chen, H.[Houjin], Peng, Y.H.[Ya-Hui], Pan, P.[Pan],
CCAFusion: Cross-Modal Coordinate Attention Network for Infrared and Visible Image Fusion,
CirSysVideo(34), No. 2, February 2024, pp. 866-881.
IEEE DOI 2402
Image fusion, Feature extraction, Task analysis, Transforms, Generative adversarial networks, Decoding, Dictionaries, multiple constrained loss function BibRef

Liu, K.[Kuizhuang], Li, M.[Min], Zuo, E.[Enguang], Chen, C.[Chen], Chen, C.[Cheng], Wang, B.[Bo], Wang, Y.L.[Yun-Ling], Lv, X.Y.[Xiao-Yi],
ASFFuse: Infrared and visible image fusion model based on adaptive selection feature maps,
PR(149), 2024, pp. 110226.
Elsevier DOI Code:
WWW Link. 2403
Image fusion, Adaptive selection feature maps, Feature enhancement, Texture loss BibRef

Yang, X.[Xin], Huo, H.T.[Hong-Tao], Li, C.[Chang], Liu, X.W.[Xiao-Wen], Wang, W.X.[Wen-Xi], Wang, C.[Cheng],
Semantic perceptive infrared and visible image fusion Transformer,
PR(149), 2024, pp. 110223.
Elsevier DOI 2403
Infrared image, Visible image, Transformer, Long-range dependency, Local feature, Semantic perceptive, Image fusion BibRef

Tang, L.F.[Lin-Feng], Chen, Z.[Ziang], Huang, J.[Jun], Ma, J.Y.[Jia-Yi],
CAMF: An Interpretable Infrared and Visible Image Fusion Network Based on Class Activation Mapping,
MultMed(26), 2024, pp. 4776-4791.
IEEE DOI 2403
Image fusion, Feature extraction, Transforms, Image reconstruction, Deep learning, Task analysis, Pollution measurement BibRef

Yang, C.X.[Chen-Xuan], He, Y.[Yunan], Sun, C.[Ce], Chen, B.K.[Bing-Kun], Cao, J.[Jie], Wang, Y.T.[Yong-Tian], Hao, Q.[Qun],
Multi-scale convolutional neural networks and saliency weight maps for infrared and visible image fusion,
JVCIR(98), 2024, pp. 104015.
Elsevier DOI 2402
Infrared and visible images, Image fusion, CNN, Guided filter, Saliency, Weight assignment BibRef

Chen, W.Y.[Wei-Yi], Miao, L.[Lingjuan], Wang, Y.H.[Yu-Hao], Zhou, Z.Q.[Zhi-Qiang], Qiao, Y.J.[Ya-Jun],
Infrared-Visible Image Fusion through Feature-Based Decomposition and Domain Normalization,
RS(16), No. 6, 2024, pp. 969.
DOI Link 2403
BibRef

Huang, J.[Jun], Chen, Z.[Ziang], Ma, Y.[Yong], Fan, F.[Fan], Tang, L.F.[Lin-Feng], Xiang, X.Y.[Xin-Yu],
PTET: A progressive token exchanging transformer for infrared and visible image fusion,
IVC(144), 2024, pp. 104957.
Elsevier DOI 2404
Image fusion, Transformer, Token exchanging, Infrared image, Visible image BibRef

Xia, Z.W.[Zheng-Wei], Liu, Y.[Yun], Wang, X.Y.[Xiao-Yun], Zhang, F.Y.[Fei-Yun], Chen, R.[Rui], Jiang, W.W.[Wei-Wei],
Infrared and Visible Image Fusion via Hybrid Variational Model,
IEICE(E108-D), No. 4, April 2024, pp. 569-573.
WWW Link. 2404
BibRef

Dong, A.[Aimei], Wang, L.[Long], Liu, J.[Jian], Lv, G.H.[Guo-Hua], Zhao, G.X.[Gui-Xin], Cheng, J.[Jinyong],
MFIFusion: An infrared and visible image enhanced fusion network based on multi-level feature injection,
PR(152), 2024, pp. 110445.
Elsevier DOI 2405
Image fusion, Multi-level feature injection, Attention mechanism BibRef

Li, H.F.[Hua-Feng], Liu, J.Y.[Jun-Yu], Zhang, Y.F.[Ya-Fei], Liu, Y.[Yu],
A Deep Learning Framework for Infrared and Visible Image Fusion Without Strict Registration,
IJCV(132), No. 5, May 2024, pp. 1625-1644.
Springer DOI 2405
BibRef

Wei, Q.C.[Qian-Cheng], Liu, Y.[Ying], Jiang, X.P.[Xiao-Ping], Zhang, B.[Ben], Su, Q.[Qiya], Yu, M.[Muyao],
DDFNet-A: Attention-Based Dual-Branch Feature Decomposition Fusion Network for Infrared and Visible Image Fusion,
RS(16), No. 10, 2024, pp. 1795.
DOI Link 2405
BibRef

Yang, Q.[Qiao], Zhang, Y.[Yu], Zhao, Z.J.[Zi-Jing], Zhang, J.[Jian], Zhang, S.[Shunli],
IAIFNet: An Illumination-Aware Infrared and Visible Image Fusion Network,
SPLetters(31), 2024, pp. 1374-1378.
IEEE DOI 2405
Image fusion, Lighting, Feature extraction, Brightness, Task analysis, Image color analysis, Visualization, illumination enhancement BibRef

Li, D.Y.[Dong-Yang], Nie, R.[Rencan], Cao, J.[Jinde], Zhang, G.[Gucheng], Jin, B.[Biaojian],
S2CANet: A self-supervised infrared and visible image fusion based on co-attention network,
SP:IC(125), 2024, pp. 117131.
Elsevier DOI 2405
Infrared and visible image fusion, Self-supervised, Co-attention, Weighted fidelity loss BibRef

Li, G.[Guofa], Lin, Y.J.[Yong-Jie], Ouyang, D.[Delin], Li, S.[Shen], Luo, X.[Xiao], Qu, X.[Xingda], Pi, D.W.[Da-Wei], Li, S.E.[Shengbo Eben],
A RGB-Thermal Image Segmentation Method Based on Parameter Sharing and Attention Fusion for Safe Autonomous Driving,
ITS(25), No. 6, June 2024, pp. 5122-5137.
IEEE DOI 2406
Feature extraction, Convolution, Decoding, Semantic segmentation, Autonomous vehicles, Semantics, Transformers, Autonomous driving, image fusion BibRef

Yang, K.X.[Kai-Xuan], Xiang, W.[Wei], Chen, Z.[Zhenshuai], Zhang, J.[Jian], Liu, Y.P.[Yun-P#1ng],
A review on infrared and visible image fusion algorithms based on neural networks,
JVCIR(101), 2024, pp. 104179.
Elsevier DOI 2406
Image fusion, Neural network, Infrared and visible images, Image processing BibRef

Setiawan, Y.[Yudi], Kustiyo, K.[Kustiyo], Hudjimartsu, S.A.[Sahid Agustian], Purwanto, J.[Judin], Rovani, R.[Riva], Tosiani, A.[Anna], Usman, A.B.[Ahmad Basyiruddin], Kartika, T.[Tatik], Indriasari, N.[Novie], Prasetyo, L.B.[Lilik Budi], Margono, B.A.[Belinda Arunarwati],
Evaluating Visible-Infrared Imaging Radiometer Suite Imagery for Developing Near-Real-Time Nationwide Vegetation Cover Monitoring in Indonesia,
RS(16), No. 11, 2024, pp. 1958.
DOI Link 2406
BibRef

Xu, J.[Jing], Liu, Z.J.[Zhen-Jin], Fang, M.[Ming],
An infrared and visible image fusion network based on multi-scale feature cascades and non-local attention,
IET-IPR(18), No. 8, 2024, pp. 2114-2125.
DOI Link 2406
convolutional neural nets, feature extraction, image fusion, image reconstruction BibRef

Liu, K.Z.[Kui-Zhuang], Li, M.[Min], Chen, C.[Cheng], Rao, C.W.[Cheng-Wei], Zuo, E.G.[En-Guang], Wang, Y.L.[Yun-Ling], Yan, Z.W.[Zi-Wei], Wang, B.[Bo], Chen, C.[Chen], Lv, X.Y.[Xiao-Yi],
DSFusion: Infrared and visible image fusion method combining detail and scene information,
PR(154), 2024, pp. 110633.
Elsevier DOI Code:
WWW Link. 2406
Image fusion, Local attention mechanism, Improved channel attention mechanism, Loss function BibRef

Xu, S.P.[Shao-Ping], Zhou, C.F.[Chang-Fei], Xiao, J.[Jian], Tao, W.[Wuyong], Dai, T.Y.[Tian-Yu],
A dual-branch infrared and visible image fusion network using progressive image-wise feature transfer,
JVCIR(102), 2024, pp. 104190.
Elsevier DOI Code:
WWW Link. 2407
Infrared and visible image fusion, Dual-branch fusion network, Progressive image-wise feature transfer, Transformer module, CLIP loss BibRef

Gao, L.N.[Ling-Na], Nie, R.C.[Ren-Can], Cao, J.[Jinde], Zhang, G.C.[Gu-Cheng],
DFG-HCEN: A distinctive-feature guided and hierarchical channel enhanced network-based infrared and visible image fusion,
IVC(148), 2024, pp. 105115.
Elsevier DOI 2407
Infrared and visible image fusion, Unsupervised learning, Feature guided-based hierarchical channel enhanced module, A hybrid loss BibRef

Shen, S.[Sen], Zhang, T.[Taotao], Dong, H.[Haidi], Yuan, S.Z.[Sheng-Zhi], Li, M.[Min], Xiao, R.K.[Ren-Kai], Zhang, X.H.[Xiao-Hui],
ADF-Net: Attention-guided deep feature decomposition network for infrared and visible image fusion,
IET-IPR(18), No. 10, 2024, pp. 2774-2787.
DOI Link 2408
image fusion BibRef

Fang, A.Q.[Ai-Qing], Li, Y.[Ying],
Dynamic and static fusion mechanisms of infrared and visible images,
PR(155), 2024, pp. 110689.
Elsevier DOI 2408
Image fusion, Dynamic fusion, Static fusion, Deep learning BibRef

Tian, J.[Jia], Sun, D.[Dong], Gao, Q.W.[Qing-Wei], Lu, Y.X.[Yi-Xiang], Bao, M.[Muxi], Zhu, D.[De], Zhao, D.W.[Da-Wei],
A novel infrared and visible image fusion algorithm based on global information-enhanced attention network,
IVC(149), 2024, pp. 105161.
Elsevier DOI 2408
Image fusion, Attention mechanism, Global information, Feature enhancement BibRef

Xing, M.L.[Meng-Liang], Liu, G.[Gang], Tang, H.J.[Hao-Jie], Qian, Y.[Yao], Zhang, J.[Jun],
CFNet: An Infrared and Visible Image Compression Fusion Network,
PR(156), 2024, pp. 110774.
Elsevier DOI Code:
WWW Link. 2408
Image fusion, Image compression, Variational autoencoder, Transformer, Region of interest BibRef

Chen, X.X.[Xiao-Xuan], Xu, S.W.[Shu-Wen], Hu, S.[Shaohai], Ma, X.L.[Xiao-Le],
MGFA: A multi-scale global feature autoencoder to fuse infrared and visible images,
SP:IC(128), 2024, pp. 117168.
Elsevier DOI 2409
Image fusion, Object detection, Autoencoder, Global information, Multi-scale feature BibRef

Liu, X.W.[Xiao-Wen], Huo, H.T.[Hong-Tao], Yang, X.[Xin], Li, J.[Jing],
A three-dimensional feature-based fusion strategy for infrared and visible image fusion,
PR(157), 2025, pp. 110885.
Elsevier DOI 2409
Image fusion, Contrastive learning, Convolution neural network BibRef

Zhao, G.P.[Gen-Ping], Hu, Z.Y.[Zhu-Yong], Feng, S.[Silu], Wang, Z.[Zhuowei], Wu, H.[Heng],
GLFuse: A Global and Local Four-Branch Feature Extraction Network for Infrared and Visible Image Fusion,
RS(16), No. 17, 2024, pp. 3246.
DOI Link 2409
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Gao, X.Y.[Xue-Yan], Liu, S.G.[Shi-Guang],
BCMFIFuse: A Bilateral Cross-Modal Feature Interaction-Based Network for Infrared and Visible Image Fusion,
RS(16), No. 17, 2024, pp. 3136.
DOI Link 2409
BibRef

Li, S.Y.[Shu-Ying], Han, M.[Muyi], Qin, Y.M.[Yue-Mei], Li, Q.[Qiang],
Self-Attention Progressive Network for Infrared and Visible Image Fusion,
RS(16), No. 18, 2024, pp. 3370.
DOI Link 2410
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Kang, J.[Jihun], Horita, D.[Daichi], Tsubota, K.[Koki], Aizawa, K.[Kiyoharu],
Restorable Visible and Infrared Image Fusion,
ICIP23(1560-1564)
IEEE DOI 2312
BibRef

Liu, R.[Renhe], Wang, H.[Han], Du, S.[Shan], Liu, Y.[Yu],
A Visible and Infrared Image Fusion Framework Based on Dual-Path Encoder-Decoder and Multi-Scale Discrete Wavelet Transform,
ICIP23(1995-1999)
IEEE DOI 2312
BibRef

Zhu, R.X.[Ruo-Xi], Ling, Y.[Yi], Xiong, X.K.[Xian-Kui], Xu, D.[Dong], Zhu, X.P.[Xuan-Peng], Fan, Y.[Yibo],
Luminance-Preserving Visible and Near-Infrared Image Fusion Network with Edge Guidance,
ICIP23(1155-1159)
IEEE DOI 2312
BibRef

Jin, H.Y.[Hai-Yan], Yang, Y.[Yue], Su, H.[Haonan], Xiao, Z.L.[Zhao-Lin], Wang, B.[Bin],
Low Light RGB and IR Image Fusion with Selective CNN-Transformer Network,
ICIP23(1255-1259)
IEEE DOI 2312
BibRef

Gao, X.[Xiang], Lv, G.H.[Guo-Hua], Dong, A.[Aimei], Wei, Z.H.[Zhong-He], Cheng, J.Y.[Jin-Yong],
L2fusion: Low-Light Oriented Infrared and Visible Image Fusion,
ICIP23(2405-2409)
IEEE DOI 2312
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Yu, H.[Hao], Cheng, X.[Xu], Peng, W.[Wei],
TOPLight: Lightweight Neural Networks with Task-Oriented Pretraining for Visible-Infrared Recognition,
CVPR23(3541-3550)
IEEE DOI 2309
BibRef

Han, Q.Q.[Qian-Qian], Xi, R.[Runping], Chen, Q.[Qian],
Infrared and Visible Image Fusion Based on Biological Vision,
ICIVC22(694-701)
IEEE DOI 2301
Visualization, Fuses, Convolution, Feature extraction, Decoding, Biological information theory, Image fusion, Biological Vision, Dual-mode cellular mechanism BibRef

Lu, C.K.[Chang-Kun], Zhou, H.B.[Hua-Bing],
Semantic Injection Infrared and Visible Image Fusion Via a Disentangled Representation Network,
ICRVC22(31-36)
IEEE DOI 2301
Image sensors, Fuses, Semantics, Sensor fusion, Generators, Sensors, deep learning, infrared images, visible images, feature decoupling, semantic injection BibRef

Lin, X.P.[Xiao-Peng], Zhou, G.X.[Guan-Xing], Zeng, W.H.[Wei-Hong], Tu, X.T.[Xiao-Tong], Huang, Y.[Yue], Ding, X.H.[Xing-Hao],
A Self-Supervised Method for Infrared and Visible Image Fusion,
ICIP22(2376-2380)
IEEE DOI 2211
Deep learning, Loss measurement, Task analysis, Image fusion, Image enhancement, fusion measurement, image fusion, image enhancement loss function BibRef

Drouin, M.A.[Marc-Antoine], Fournier, J.[Jonathan],
Infrared and Visible Image Registration for Airborne Camera Systems,
ICIP22(951-955)
IEEE DOI 2211
Image registration, Surveillance, Streaming media, Reconnaissance, Cameras, Registers, Synchronization, image fusion, airborne imagery BibRef

Ye, M.[Mang], Ruan, W.J.[Wei-Jian], Du, B.[Bo], Shou, M.Z.[Mike Zheng],
Channel Augmented Joint Learning for Visible-Infrared Recognition,
ICCV21(13547-13556)
IEEE DOI 2203
Measurement, Image color analysis, Robustness, Task analysis, Standards, Action and behavior recognition, Vision applications and systems BibRef

Liu, N.[Ni], Yang, B.[Bin],
Infrared and Visible Image Fusion Based on TRPCA and Visual Saliency Detection,
ICIVC21(13-19)
IEEE DOI 2112
Degradation, Visualization, Tensors, Fuses, Indexes, Image fusion, Image reconstruction, image fusion, TRPCA, local energy, visual saliency detection BibRef

Ng, K.C.[Kim C.], Shen, J.L.[Jing-Lin], Ho, C.M.[Chiu Man],
A System for Fusing Color and Near-Infrared Images in Radiance Domain,
AIM21(2021-2030)
IEEE DOI 2112
Image quality, Privacy, Ethics, Image color analysis, Fuses, Clothing, Pipelines BibRef

Jia, X.Y.[Xin-Yu], Zhu, C.[Chuang], Li, M.Z.[Min-Zhen], Tang, W.Q.[Wen-Qi], Zhou, W.L.[Wen-Li],
LLVIP: A Visible-infrared Paired Dataset for Low-light Vision,
RLQ21(3489-3497)
IEEE DOI 2112
Visualization, Image registration, Annotations, Task analysis, Image fusion BibRef

Mei, L.[Lin], Jung, C.[Cheolkon],
Deep Fusion of RGB and NIR Paired Images Using Convolutional Neural Networks,
ICPR21(6802-6803)
IEEE DOI 2105
Visualization, Runtime, Image color analysis, Fuses, Noise reduction, Brightness, Pattern recognition BibRef

Fu, Y.[Yu], Wu, X.J.[Xiao-Jun],
A Dual-Branch Network for Infrared and Visible Image Fusion,
ICPR21(10675-10680)
IEEE DOI 2105
Deep learning, Fuses, Image synthesis, Semantics, Feature extraction, Decoding, Data mining BibRef

Zheng, J., Jung, C., Yu, S.,
Low Light Image Enhancement by Multispectral Fusion of RGB and NIR Images,
ICIP20(2541-2545)
IEEE DOI 2011
Reliability, Image color analysis, Colored noise, Imaging, Noise reduction, Linear systems, Image enhancement, Image fusion, total variation BibRef

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Bvtnet: Multi-label Multi-class Fusion of Visible and Thermal Camera for Free Space and Pedestrian Segmentation,
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Zhu, J., Ye, Z., Xu, Y., Hoegner, L., Stilla, U.,
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Zhang, X., Ye, P., Xiao, G.,
VIFB: A Visible and Infrared Image Fusion Benchmark,
PBVS20(468-478)
IEEE DOI 2008
Image fusion, Benchmark testing, Machine learning, Libraries, Signal processing algorithms, Performance evaluation BibRef

Yang, S., Yu, S., Zhao, B., Zhao, B.,
Reducing the feature divergence of RGB and near-infrared images using Switchable Normalization,
AgriVision20(206-211)
IEEE DOI 2008
Task analysis, Computational modeling, Pattern recognition, Switches, Agriculture, Semantics BibRef

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Fusion of thermal and visible colour images for robust detection of people in forests,
IVCNZ19(1-6)
IEEE DOI 2004
image colour analysis, image fusion, image sensors, infrared imaging, temperature measurement, temperature sensors, unstructured outdoor environments BibRef

Dadras Javan, F., Savadkouhi, M.,
Thermal 3d Models Enhancement Based On Integration With Visible Imagery,
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Dahaghin, M., Samadzadegan, F., Dadras Javan, F.,
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Treible, W., Saponaro, P., Kambhamettu, C.,
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ICIP19(1307-1311)
IEEE DOI 1910
Multispectral imaging, Image Matching, Neural networks BibRef

Nyberg, A.[Adam], Eldesokey, A.[Abdelrahman], Bergström, D.[David], Gustafsson, D.[David],
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Li, Y., Tan, J., Zhang, Y., Liang, W., He, H.,
Spatial Calibration for Thermal-RGB Cameras and Inertial Sensor System,
ICPR18(2295-2300)
IEEE DOI 1812
Cameras, Calibration, Lighting, Acceleration, Thermal sensors, Distortion, Feature extraction BibRef

Su, H., Jung, C.,
Multi-Spectral Fusion and Denoising of RGB and NIR Images Using Multi-Scale Wavelet Analysis,
ICPR18(1779-1784)
IEEE DOI 1812
Noise reduction, Noise measurement, Wavelet analysis, Smoothing methods, Estimation, Discrete wavelet transforms, Color BibRef

Li, H.[Hui], Wu, X.J.[Xiao-Jun], Kittler, J.V.[Josef V.],
Infrared and Visible Image Fusion using a Deep Learning Framework,
ICPR18(2705-2710)
IEEE DOI 1812
Feature extraction, Image fusion, Image reconstruction, Pattern recognition, Tools, Task analysis BibRef

Lu, G., Yu, H., Yuan, C.,
Getting Rid of Night: Thermal Image Classification Based on Feature Fusion,
ICPR18(2827-2832)
IEEE DOI 1812
Feature extraction, Image edge detection, Cameras, Histograms, Task analysis, Shape, Temperature BibRef

Liu, S., John, V., Blasch, E., Liu, Z., Huang, Y.,
IR2VI: Enhanced Night Environmental Perception by Unsupervised Thermal Image Translation,
PBVS18(1234-12347)
IEEE DOI 1812
Training, Image fusion, Generators, Night vision, Task analysis, Semantics BibRef

Liu, Z., Feng, Y.,
Infrared and Visible Image Fusion Based on Compressive Sensing and OSS-ICA-Bases,
ICIP18(1852-1856)
IEEE DOI 1809
Image fusion, Discrete wavelet transforms, Compressed sensing, Image reconstruction, Indexes, Image fusion, NSST, CS, OSS-ICA-bases, infrared and visible images BibRef

Awad, M., Elliethy, A., Aly, H.A.,
A Real-Time FPGA Implementation of Visible/Near Infrared Fusion Based Image Enhancement,
ICIP18(3968-3972)
IEEE DOI 1809
Field programmable gate arrays, Real-time systems, Clocks, Image enhancement, Cameras, Estimation, Shift registers, FPGA, BibRef

Gois, J.N., da Silva, E.A.B., Pagliari, C.L., Perez, M.M.,
Fusion of Infrared and Visible-Light Videos Using Motion-Compensated Temporal Sub-Band Decompositions,
WACV18(93-101)
IEEE DOI 1806
image fusion, image registration, motion compensation, spatiotemporal phenomena, video signal processing, Videos BibRef

Truong, T.P., Yamaguchi, M., Mori, S., Nozick, V., Saito, H.,
Registration of RGB and Thermal Point Clouds Generated by Structure From Motion,
MSF17(419-427)
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Calibration, Cameras, Distortion, Image reconstruction, Thermal sensors, BibRef

Toque, J.A.[Jay Arre], Okumura, K.[Koji], Shimbata, Y.[Yashuhide], Ide-Ektessabi, A.[Ari],
Visualization of Subsurface Features in Oil Paintings Using High-Resolution Visible and Near Infrared Scanned Images,
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Yoshida, K.[Kyohei], Wang, P.[Peng], Toque, J.A.[Jay Arre], Toiya, M.[Masahiro], Ide-Ektessabi, A.[Ari],
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Tsuchida, M.[Masaru], Yano, K.[Keiji], Hiramatsu, K.[Kaoru], Kashino, K.[Kunio],
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He, G., Wei, Y.,
An Anti-noise Fusion Method for the Infrared and the Visible Image Based upon Sparse Representation,
CMVIT17(12-17)
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image denoising BibRef

Li, W., Sun, X., Wu, F.,
Enhancing nighttime surveillance video via gradient fusion,
VCIP15(1-4)
IEEE DOI 1605
Cameras BibRef

Cheng, K.S.[Kai-Sheng], Lin, H.Y.[Huei-Yung],
Automatic target recognition by infrared and visible image matching,
MVA15(312-315)
IEEE DOI 1507
Cameras BibRef

Nakagawa, W.[Wataru], Matsumoto, K.[Kazuki], de Sorbier, F.[Francois], Sugimoto, M.[Maki], Saito, H.[Hideo], Senda, S.[Shuji], Shibata, T.[Takashi], Iketani, A.[Akihiko],
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Yang, M.Y.[Michael Ying], Qiang, Y.[Yu], Rosenhahn, B.[Bodo],
A Global-to-Local Framework for Infrared and Visible Image Sequence Registration,
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Cameras BibRef

Saponaro, P.[Philip], Sherbondy, K.[Kelly], Kambhamettu, C.[Chandra],
Concealed Target Detection with Fusion of Visible and Infrared,
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Zhang, H.[Hong], Chen, Q.J.[Quan-Jun], Yuan, D.[Ding], You, Y.H.[Yu Hu], Sun, M.G.[Min-Gui],
Fusion of Infrared and Visible Images Using 2DPCA Bases,
ACPR13(596-600)
IEEE DOI 1408
feature extraction BibRef

Nguyen, C.T., Havlicek, J.P.,
Linear adaptive infrared image fusion,
Southwest14(117-120)
IEEE DOI 1406
image fusion BibRef

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Weinmann, M., Hoegner, L., Leitloff, J., Stilla, U., Hinz, S., Jutzi, B.,
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Yang, G.[Guang], Yin, Y.F.[Ya-Feng], Man, H.[Hong],
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Yoo, Y.J.[Young-Jin], Choe, W.H.[Won-Hee], Kwon, J.H.[Jae-Hyun], Park, S.C.[Sung-Chan], Lee, S.D.[Seong-Deok], Kim, C.Y.[Chang-Yong],
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Qu, Y.H.[Yong-Hua], Zhang, Y.Z.[Yu-Zhen],
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Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
RGB and Thermal Fusion for Object Extraction .