[1] LAND E H.The retinex[J].American Scientist, 1964, 52(2):247-253, 255-264. [2] JOBSON D J, RAHMAN Z, WOODELL G A.Properties and performance of a center/surround retinex[J].IEEE Transactions on Image Processing, 1997, 6(3):451-462. [3] JOBSON D J, RAHMAN Z, WOODELL G A.A multiscale retinex for bridging the gap between color images and the human observation of scenes[J].IEEE Transactions on Image Processing, 1997, 6(7):965-976. [4] ZJHANG S, ZENG P, LUO X, et al.Multi-scale retinex with color restoration and detail compensation[J].Journal of Xiʼan Jiaotong University, 2012, 46(4):32-37. [5] WANG S, ZHENG J, HU H M, et al.Naturalness preserved enhancement algorithm for non-uniform illumination images[J].IEEE Transactions on Image Processing, 2013, 22(9):3538-3548. [6] DONG X, WANG G, PANG Y, et al.Fast efficient algorithm for enhancement of low lighting video[C]//Proceedings of 2011 IEEE International Conference on Multimedia and Expo.Washington D.C., USA:IEEE Press, 2011:346-368. [7] LI L, WANG R, WANG W, et al.A low-light image enhancement method for both denoising and contrast enlarging[C]//Proceedings of IEEE International Conference on Image Processing.Washington D.C., USA:IEEE Press, 2015:765-779. [8] 刘超, 张晓晖.超低照度下微光图像的深度卷积自编码网络复原[J].光学精密工程, 2018, 26(4):951-961. LIU C, ZHANG X H.Depth convolution autoencoding network restoration of low-light level images under ultra-low illumination[J].Optics and Precision Engineering, 2018, 26(4):951-961.(in Chinese) [9] CHEN C, CHEN Q, XU J, et al.Learning to see in the dark[C]//Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition.Washington D.C., USA:IEEE Press, 2018:3291-3300. [10] DENG X, LOPEZ-MARTINEZ C.On the use of the l(2)-norm for texture analysis of polarimetric SAR data[J].IEEE Transactions on Geoence and Remote Sensing, 2016, 54(11):6385-6398. [11] 刘敏, 夏海英, 周奕捷, 等.基于Retinex非均匀光照图像的照度分量估计[J].电视技术, 2019, 43(4):32-35. LIU M, XIA H Y, ZHOU Y J, et al.Illumination component estimation based on Retinex non-uniform illumination image[J].Television Technology, 2019, 43(4):32-35.(in Chinese) [12] XU L, YAN Q, XIA Y, et al.Structure extraction from texture via relative total variation[J].ACM Transactions on Graphics, 2012, 31(6):112-123. [13] 杨先凤, 李小兰, 贵红军.改进的自适应伽马变换图像增强算法仿真[J].计算机仿真, 2020, 37(5):241-245. YANG X F, LI X L, GUI H J.Improved adaptive gamma transform image enhancement algorithm simulation[J].Computer Simulation, 2020, 37(5):241-245.(in Chinese) [14] HORE A, ZIOU D.Image quality metrics:PSNR vs.SSIM[C]//Proceedings of the 20th International Conference on Pattern Recognition.Washington D.C., USA:IEEE Press, 2010:2366-2369. [15] WANG Z, BOVIK A C, SHEIKH H R, et al.Image quality assessment:from error visibility to structural similarity[J].IEEE Transactions on Image Processing, 2004, 13(4):600-612. [16] YEGANEH H, WANG Z.Objective quality assessment of tone-mapped images[J].IEEE Transactions on Image Processing, 2013, 22(2):657-667. [17] MITTAL A, FELLOW.Making a ‘completely blind’ image quality analyzer[J].IEEE Signal Processing Letters, 2013, 20(3):209-212. [18] WANG S, MA K, YEGANEH H, et al.A patch-structure representation method for quality assessment of contrast changed images[J].IEEE Signal Processing Letters, 2015, 22(12):2387-2390. [19] WEI C, WANG W J, YANG W H, et al.Deep retinex decomposition for low-light enhancement[EB/OL].[2020-07-10].https://arxiv.org/abs/1808.04560v1. [20] GUO X J, YU L, LING H B.LIME:low-light image enhancement via illumination map estimation[J].IEEE Transactions on Image Processing, 2017, 26(2):982-993. [21] FU X, ZENG D, HUANG Y, et al.A weighted variational model for simultaneous reflectance and illumination estimation[C]//Proceedings of IEEE International Conference on Computer Vision & Pattern Recognition.Washington D.C., USA:IEEE Press, 2016:452-468. [22] 田会娟, 蔡敏鹏, 关涛, 等.基于YCbCr颜色空间的Retinex低照度图像增强方法研究[J].光子学报, 2020, 49(2):173-184. TIAN H J, CAI M P, GUAN T, et al.Retinex low-light image enhancement method based on YCbCr colorspace[J].Acta Photonica Sinica, 2020, 49(2):173-184.(in Chinese) |