Computer Science ›› 2022, Vol. 49 ›› Issue (6): 199-209.doi: 10.11896/jsjkx.210400092
• Computer Graphics & Multimedia • Previous Articles Next Articles
ZHAO Zheng-peng1, LI Jun-gang1, PU Yuan-yuan1,2
CLC Number:
[1] REFAEL C.Digital image processing(2 Edition)[M].Translated by RUAN Q Q.Beijing:Publishing House of Electronics Industry,2003. [2] MOU Q,WEI Y Y,LI J,et al.Research on Improved Retinex Low Illumination Image Enhancement Algorithm[J].Journal of Harbin Engineering University,2018,39(12):2001-2010. [3] LI Q Z,LIU Q.Adaptive enhancement algorithm for low illumination image based on wavelet transform[J].Chinese Journal of Lasers,2015,42(2):280-286. [4] ZHANG Y J.Image Engineering Volume-Image Processing and Analysis[M].Beijing:Tsinghua University Press,2006. [5] JAIN A.Fundamentals of Digital Image Processing[M].Englewood Cliffs,NJ:Prentice Hall,1989. [6] IBRAHIM H,KONG N S P.Brightness Preserving DynamicHistogram Equalization for Image Contrast Enhancement[J].IEEE Transactions on Consumer Electronics,2007,53(4):1752-1758. [7] CHAO W,YE Z.Brightness preserving histogram equalization with maximum entropy:a variational perspective[J].IEEE Transactions on Consumer Electronics,2005,51(4):1326-1334. [8] CHEN S D,RAMLI A R.Minimum mean brightness error Bi-histogram equalization in contrast enhancement[J].IEEE Transactions on Consumer Electronics,2003,49(4):1310. [9] YUE H,YANG J,SUN X,et al.Contrast enhancement based on intrinsic image decomposition[J].IEEE Transactions on Image Processing,2017,26(8):3981-3994. [10] LAND E H,MCCANN J J.Lightness and retinextheory[J].Journal of the Optical Society of America,1971,61(1):1-11. [11] JOBSON D J,RAHMAN Z U,WOODELL G A.Properties and Performance of a Center/Surround Retinex[J].IEEE Transactions on Image Processing,1997,6(3):451-462. [12] RAHMAN Z U,JOBSON D J,WOODELL G W.Multiscale retinex for color rendition and dynamic range compression[J].Proc Spie,1996,2847:183-191. [13] COOPER T J,BAQAI F A.Analysis and extensions of theFrankle-McCann Retinex algorithm[J].Journal of Electronic Imaging,2004,13(1):85-92. [14] LORE K G,AKINTAYO A,SARKAR S.LLNet:A DeepAutoencoder Approach to Natural Low-light Image Enhancement[J].Pattern Recognition,2017,61:650-662. [15] MA H Q,MA S P,XU Y L,et al.Low-light image enhancement based on deep convolutional neural network[J].Acta Optica Sinica,2019,39(2):91-100. [16] SHEN L,YUE Z,FENG F,et al.MSR-net:Low-light Image Enhancement Using Deep Convolutional Network[J].arXiv:1711.02488. [17] WEI C,WANG W,YANG W,et al.Deep retinex decomposition for low-light enhancement[C]//British Machine Vision Confe-rence(BMVC).2018. [18] ZHANG Y,ZHANG J,GUO X,et al.Kindling the Darkness:A Practical Low-Light Image Enhancer[C]//ACM Multimedia.2019:1632-1640. [19] WU R Y,WANG D X,YUAN H C,et al.Low illuminationimage enhancement based on multi-branch fully convolutional neural network[J].Progress in Laser and Optoelectronics,2020,57(14):197-207. [20] LI J H,WNAG K.A Low-light Image Enhancement Method Based on Convolutional Neural Network[J].Journal of Jiangxi University of Science and Technology,2020,41(5):73-79. [21] CHAN S H,KHOSHABEH R,GIBSON K B,et al.An Augmented Lagrangian Method for Total Variation Video Restoration[J].IEEE Transactions on Image Processing,2011,20(11):3097-3111. [22] ZHANG K,ZUO W,CHEN Y,et al.Beyond a Gaussian Denoi-ser:Residual Learning of Deep CNN for Image Denoising[J].IEEE Transactions on Image Processing,2016,26(7):3142-3155. [23] WOO S,PARK J,LEE J Y,et al.Cbam:Convolutionalblock attention module[C]//Proceedings of the European Conference on Computer Vision(ECCV).2018:3-19. [24] MITTAL A,SOUNDARARAJAN R.Making a ‘CompletelyBlind’ Image Quality Analyzer[J].IEEE Signal Processing Letters,2013,20(3):209-212. [25] DANG-NGUYEN D T,PASQUINI C,CONOTTER V,et al.RAISE:a raw images dataset for digital image forensics[C]//ACM Multimedia Systems Conference.ACM,2015:219-224. [26] WANG S H,ZHENG J,HUH M,et al.Naturalness preserved enhancement algorithm for non-uniform illumination images[J].IEEE Transactions on Image Processing,2013,22(9):3538-3548. [27] GUO X J,LI Y,LING H B.Lime:Low-light image enhancement via illumination map estimation[J].IEEE Transactions on Image Processing,2017,26(2):982-993. [28] LEE C,LEE C,KIM C S.Contrast enhancement based on la-yered difference representation of 2D histograms[J].IEEE Transactions on Image Processing,2013,22(12):5372-5384. [29] ROTH S,BLACK M J.Fields of experts[J].International Journal of Computer Vision,2009,82(2):205-229. [30] LOH Y P,CHAN C S.Getting to know low-light images with the Exclusively Dark dataset[J].Computer Vision and Image Understanding,2019,178:30-42. [31] MA K,ZENG K,WANG Z.Perceptual Quality Assessment for Multi-Exposure Image Fusion[J].IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society,2015,24(11):3345-3356. [32] LV F F,LU F,WU J H,et al.MBLLEN:Low-light Image/Video Enhancement Using CNNs[C]//British Machine Vision Conference(BMVC).2018. [33] FU X,ZENG D,HUANG Y,et al.A Weighted VariationalModel for Simultaneous Reflectance and Illumination Estimation[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).IEEE,2016:2782-2790. [34] YING Z,LI G,GAO W.A bio-inspired multi-exposure fusion framework for low-light image enhancement[J].arXiv:1711.00591,2017. [35] LI M,LIU J,YANG W,et al.Structure-Revealing Low-LightImage Enhancement Via Robust Retinex Model[J].IEEE Transactions on Image Processing,2018,27(6):2828-2841. [36] Al-AMEEN Z.Nighttime image enhancement using a new illumination boost algorithm[J].Image Processing,IET,2019,13(8):1314-1320. [37] DAI Q,PU Y F,RAHMAN Z,et al.Fractional-Order FusionModel for Low-Light Image Enhancement[J].Symmetry,2019,11(4):574-591. [38] LU K,ZHANG L.TBEFN:A Two-Branch Exposure-Fusion Network for Low-Light Image Enhancement[J].IEEE Transactions on Multimedia,2021,23:4093-4105. [39] HAO S,HAN X,GUO Y,et al.Low-Light Image Enhancement with Semi-Decoupled Decomposition[J].IEEE Transactions on Multimedia,2020,22(12):3025-3038. |
[1] | ZHOU Le-yuan, ZHANG Jian-hua, YUAN Tian-tian, CHEN Sheng-yong. Sequence-to-Sequence Chinese Continuous Sign Language Recognition and Translation with Multi- layer Attention Mechanism Fusion [J]. Computer Science, 2022, 49(9): 155-161. |
[2] | CHEN Yong-quan, JIANG Ying. Analysis Method of APP User Behavior Based on Convolutional Neural Network [J]. Computer Science, 2022, 49(8): 78-85. |
[3] | ZHU Cheng-zhang, HUANG Jia-er, XIAO Ya-long, WANG Han, ZOU Bei-ji. Deep Hash Retrieval Algorithm for Medical Images Based on Attention Mechanism [J]. Computer Science, 2022, 49(8): 113-119. |
[4] | DAI Zhao-xia, LI Jin-xin, ZHANG Xiang-dong, XU Xu, MEI Lin, ZHANG Liang. Super-resolution Reconstruction of MRI Based on DNGAN [J]. Computer Science, 2022, 49(7): 113-119. |
[5] | LIU Yue-hong, NIU Shao-hua, SHEN Xian-hao. Virtual Reality Video Intraframe Prediction Coding Based on Convolutional Neural Network [J]. Computer Science, 2022, 49(7): 127-131. |
[6] | XU Ming-ke, ZHANG Fan. Head Fusion:A Method to Improve Accuracy and Robustness of Speech Emotion Recognition [J]. Computer Science, 2022, 49(7): 132-141. |
[7] | WU Zi-bin, YAN Qiao. Projected Gradient Descent Algorithm with Momentum [J]. Computer Science, 2022, 49(6A): 178-183. |
[8] | YANG Yue, FENG Tao, LIANG Hong, YANG Yang. Image Arbitrary Style Transfer via Criss-cross Attention [J]. Computer Science, 2022, 49(6A): 345-352. |
[9] | YANG Jian-nan, ZHANG Fan. Classification Method for Small Crops Combining Dual Attention Mechanisms and Hierarchical Network Structure [J]. Computer Science, 2022, 49(6A): 353-357. |
[10] | ZHANG Jia-hao, LIU Feng, QI Jia-yin. Lightweight Micro-expression Recognition Architecture Based on Bottleneck Transformer [J]. Computer Science, 2022, 49(6A): 370-377. |
[11] | WANG Jian-ming, CHEN Xiang-yu, YANG Zi-zhong, SHI Chen-yang, ZHANG Yu-hang, QIAN Zheng-kun. Influence of Different Data Augmentation Methods on Model Recognition Accuracy [J]. Computer Science, 2022, 49(6A): 418-423. |
[12] | SUN Jie-qi, LI Ya-feng, ZHANG Wen-bo, LIU Peng-hui. Dual-field Feature Fusion Deep Convolutional Neural Network Based on Discrete Wavelet Transformation [J]. Computer Science, 2022, 49(6A): 434-440. |
[13] | HU Fu-yuan, WAN Xin-jun, SHEN Ming-fei, XU Jiang-lang, YAO Rui, TAO Zhong-ben. Survey Progress on Image Instance Segmentation Methods of Deep Convolutional Neural Network [J]. Computer Science, 2022, 49(5): 10-24. |
[14] | XU Hua-chi, SHI Dian-xi, CUI Yu-ning, JING Luo-xi, LIU Cong. Time Information Integration Network for Event Cameras [J]. Computer Science, 2022, 49(5): 43-49. |
[15] | LIU Lin-yun, CHEN Kai-yan, LI Xiong-wei, ZHANG Yang, XIE Fang-fang. Overview of Side Channel Analysis Based on Convolutional Neural Network [J]. Computer Science, 2022, 49(5): 296-302. |
|