Liu, C.J.[Chang-Jiang],
Cheng, I.[Irene],
Zhang, Y.[Yi],
Basu, A.[Anup],
Enhancement of low visibility aerial images using histogram
truncation and an explicit Retinex representation for balancing
contrast and color consistency,
PandRS(128), No. 1, 2017, pp. 16-26.
Elsevier DOI
1706
Multi-scale, Retinex
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
Gu, Z.,
Li, F.,
Fang, F.,
Zhang, G.,
A Novel Retinex-Based Fractional-Order Variational Model for Images
With Severely Low Light,
IP(29), 2020, pp. 3239-3253.
IEEE DOI
2002
Retinex, low-light image, fractional-order, variational model,
image enhancement, reflectance, illumination
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
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
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
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
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
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, Image enhancement, Task analysis, Histograms,
Cameras, Low-light image enhancement, zero-reference
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
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
Jia, F.[Fan],
Wong, H.S.[Hok Shing],
Wang, T.[Tiange],
Zeng, T.Y.[Tie-Yong],
A reflectance re-weighted Retinex model for non-uniform and low-light
image enhancement,
PR(144), 2023, pp. 109823.
Elsevier DOI
2310
Image enhancement, Variational method, Retinex model, Non-uniform enhancement
BibRef
Jia, F.[Fan],
Mao, S.[Shen],
Tai, X.C.[Xue-Cheng],
Zeng, T.Y.[Tie-Yong],
A Variational Model for Nonuniform Low-Light Image Enhancement,
SIIMS(17), No. 1, 2024, pp. 1-30.
DOI Link
2404
BibRef
Ma, Q.T.[Qian-Ting],
Wang, Y.[Yang],
Zeng, T.Y.[Tie-Yong],
A Contrast-Saturation Adaptive Model for Low-Light Image Enhancement,
SIIMS(18), No. 1, 2025, pp. 765-787.
DOI Link
2504
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
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
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
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
An, N.[Nan],
Ma, L.[Long],
Han, G.C.[Guang-Chao],
Fan, X.[Xin],
Liu, R.S.[Ri-Sheng],
Striving for Faster and Better: A One-Layer Architecture With Auto
Re-Parameterization for Low-Light Image Enhancement,
CirSysVideo(35), No. 8, August 2025, pp. 7455-7470.
IEEE DOI Code:
WWW Link.
2508
Visualization, Image enhancement, Computational efficiency,
Lighting, Reflectivity, Computational modeling, Optimization,
tiered architecture search
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
Ma, L.[Long],
Ma, T.Y.[Teng-Yu],
Xu, C.P.[Cheng-Pei],
Liu, J.Y.[Jin-Yuan],
Fan, X.[Xin],
Luo, Z.X.[Zhong-Xuan],
Liu, R.S.[Ri-Sheng],
Learning with Self-Calibrator for Fast and Robust Low-Light Image
Enhancement,
PAMI(47), No. 10, October 2025, pp. 9095-9112.
IEEE DOI
2510
Lighting, Image enhancement, Training, Visualization, Estimation,
Convergence, Architecture, Reflectivity, Optimization, low-light vision
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
Zhou, M.L.[Ming-Liang],
Wu, X.T.[Xing-Tai],
Wei, X.K.[Xue-Kai],
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
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
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
Weng, R.[Ruidi],
Zhang, Y.[Ya],
Wu, H.Y.[Han-Yang],
Wang, W.Y.[Wei-Yong],
Wang, D.Y.[Dong-Yun],
The Retinex enhancement algorithm for low-light intensity image based
on improved illumination map,
IET-IPR(18), No. 12, 2024, pp. 3381-3392.
DOI Link
2411
image denoising, image enhancement, image processing
BibRef
Chen, L.W.[Li-Wei],
Liu, Y.Y.[Yan-Yan],
Li, G.[Guoning],
Hong, J.T.[Jin-Tao],
Li, J.[Jin],
Peng, J.T.[Jian-Tao],
Double-function enhancement algorithm for low-illumination images
based on retinex theory,
JOSA-A(40), No. 2, February 2023, pp. 316-325.
DOI Link
2503
Deep learning, Image metrics, Image quality, Machine vision,
Neural networks, Wavelet transforms
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
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
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
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
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
See also Underwater Image Enhancement via LBP-Based Attention Residual Network.
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
Gao, X.Y.[Xing-Yun],
Zhang, W.B.[Wei-Bo],
Zhuang, P.X.[Pei-Xian],
Zhao, W.[Wenyi],
Zhang, W.D.[Wei-Dong],
RDANet: Retinex decomposition attention network for low-light image
enhancement,
PRL(197), 2025, pp. 175-181.
Elsevier DOI
2510
Low-light image enhancement, Cascaded attention, Retinex decomposition
BibRef
Qiang, H.[Hu],
Zhong, Y.Z.[Yu-Zhong],
Liao, Y.W.[Yi-Wei],
You, X.X.[Xing-Xing],
Zhu, Y.Q.[Yu-Qi],
Dian, S.[Songyi],
GWRetinex-Net: Gray World Retinex Network for Low-Light Image
Enhancement,
CirSysVideo(35), No. 10, October 2025, pp. 9636-9649.
IEEE DOI
2510
Lighting, Reflection, Image color analysis, Image enhancement,
Distortion, Degradation, Deep learning, Brightness, Training, Noise,
color balance
BibRef
Li, W.C.[Wen-Chao],
Wen, S.Y.[Shu-Yuan],
Zhu, J.H.[Jin-Hao],
Ou, Q.[Qiaofeng],
Guo, Y.C.[Yan-Chun],
Chen, J.[Jiabao],
Xiong, B.S.[Bang-Shu],
ZERRIN-Net: Adaptive low-light image enhancement using Retinex
decomposition and noise extraction,
SP:IC(138), 2025, pp. 117345.
Elsevier DOI Code:
WWW Link.
2509
Low-light image enhancement, Image denoise, Zero-shot learning,
Retinex decomposition
BibRef
Yi, X.P.[Xun-Peng],
Xu, H.[Han],
Zhang, H.[Hao],
Tang, L.F.[Lin-Feng],
Ma, J.Y.[Jia-Yi],
Diff-Retinex++: Retinex-Driven Reinforced Diffusion Model for
Low-Light Image Enhancement,
PAMI(47), No. 8, August 2025, pp. 6823-6841.
IEEE DOI
2507
BibRef
Earlier:
Diff-Retinex: Rethinking Low-light Image Enhancement with A
Generative Diffusion Model,
ICCV23(12268-12277)
IEEE DOI
2401
Diffusion models, Image enhancement, Image restoration,
Degradation, Lighting, Image synthesis, Noise reduction, mixture of experts
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, H.K.[Hua-Ke],
Hou, X.S.[Xing-Song],
Li, J.T.[Ju-Tao],
Yan, Y.[Yadi],
Sun, W.K.[Wen-Ke],
Zeng, X.[Xin],
Zhang, K.B.[Kai-Bing],
Cao, X.Y.[Xiang-Yong],
Multi-Scale Retinex Unfolding Network for Low-Light Image Enhancement,
MultMed(27), 2025, pp. 5709-5721.
IEEE DOI
2509
Image enhancement, Lighting, Computational modeling, Optimization,
Transformers, Image restoration, Image color analysis, Data mining,
scale-aware proximal mapping
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
Kang, S.C.[Si-Cong],
Gao, S.B.[Shuai-Bo],
Wu, W.H.[Wen-Hui],
Wang, X.[Xu],
Wang, S.[Shuoyao],
Qiu, G.P.[Guo-Ping],
Image Intrinsic Components Guided Conditional Diffusion Model for
Low-Light Image Enhancement,
CirSysVideo(34), No. 12, December 2024, pp. 13244-13256.
IEEE DOI Code:
WWW Link.
2501
Lighting, Image restoration, Reflectivity, Diffusion models,
Feature extraction, Image color analysis, Image enhancement,
retinex decomposition
BibRef
Liu, C.X.[Chun-Xiao],
Wang, Z.[Zelong],
Birch, P.[Philip],
Wang, X.[Xun],
Efficient Retinex-Based Framework for Low-Light Image Enhancement
Without Additional Networks,
CirSysVideo(35), No. 5, May 2025, pp. 4896-4909.
IEEE DOI
2505
Lighting, Degradation, Image enhancement, Image color analysis,
Estimation, Transforms, Colored noise, multiscale attention network
BibRef
Guo, R.[Ruoyu],
Pagnucco, M.[Maurice],
Song, Y.[Yang],
Exploring Multi-Feature Relationship in Retinex Decomposition for
Low-Light Image Enhancement,
MultMed(27), 2025, pp. 7271-7284.
IEEE DOI
2510
Reflectivity, Lighting, Image color analysis, Feature extraction,
Image enhancement, Training, Brightness, Unsupervised learning,
Retinex theory
BibRef
Ma, A.[Ailin],
Jiang, H.[Hai],
Liang, B.B.[Bin-Bin],
Han, S.C.[Song-Chen],
Incorporating Fourier Transformation With Diffusion Models for
Low-Light Image Enhancement,
SPLetters(32), 2025, pp. 2354-2358.
IEEE DOI
2507
Image restoration, Image reconstruction, Diffusion models,
Noise reduction, Training, Degradation, Image enhancement,
low-light image enhancement
BibRef
Jiang, H.[Hai],
Luo, A.[Ao],
Liu, X.H.[Xiao-Hong],
Han, S.C.[Song-Chen],
Liu, S.C.[Shuai-Cheng],
Lightendiffusion: Unsupervised Low-light Image Enhancement with
Latent-retinex Diffusion Models,
ECCV24(XLVIII: 161-179).
Springer DOI
2412
BibRef
Zhang, J.[Jin],
Jin, H.Y.[Hai-Yan],
Su, H.N.[Hao-Nan],
Zhang, Y.L.[Yuan-Lin],
Xiao, Z.L.[Zhao-Lin],
Wang, B.[Bin],
A CNN-Transformer Network Based SNR Guided High Frequency
Reconstruction for Low Light Image Enhancement,
ICIP24(1649-1655)
IEEE DOI
2411
Visualization, Image edge detection, Noise reduction, Transformers,
Image decomposition, Image restoration, High frequency, SNR
BibRef
Cai, Y.H.[Yuan-Hao],
Bian, H.[Hao],
Lin, J.[Jing],
Wang, H.Q.[Hao-Qian],
Timofte, R.[Radu],
Zhang, Y.L.[Yu-Lun],
Retinexformer: One-stage Retinex-based Transformer for Low-light
Image Enhancement,
ICCV23(12470-12479)
IEEE DOI Code:
WWW Link.
2401
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
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
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
BibRef
Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in
Color Constancy, Recognition, Simon Fraser Univ. (Funt and Finlayson) Papers .