Infrared Technology, Volume. 46, Issue 10, 1145(2024)
Low-light Image Enhancement via Detail Saliency Estimation
[3] [3] Touati R, Mignotte M, Dahmane M. Multimodal change detection in remote sensing images using an unsupervised pixel pairwise-based Markov random field model[J]. IEEE Transactions on Image Processing, 2019, 29: 757-767.
[4] [4] WU Xiaojian, Kim Mijin, QU Haoran, et al. Single-defect spectroscopy in the shortwave infrared[J]. Nature Communications, 2019, 10(1): 2672.
[5] [5] Saif M, Kwanten W J, Carr J A, et al. Non-invasive monitoring of chronic liver disease via near-infrared and shortwave-infrared imaging of endogenous lipofuscin[J]. Nature Biomedical Engineering, 2020, 10: 2672.
[6] [6] LI Mading, LIU Jiaying, YANG Jiaying, et al. Structure-revealing low-light image enhancement via robust Retinex model[J]. IEEE Transactions on Image Processing, 2018, 27(6): 2828-2841.
[7] [7] LI Hui, WU Xiaojun. DenseFuse: a fusion approach to infrared and visible images[J]. IEEE Transactions on Image Processing, 2018, 28(5): 2614-2623.
[8] [8] Arnob Md Masud Parvez, HUNG Nguyen, ZHU Han, et al. Compressed sensing hyperspectral imaging in the 0.9-2.5 m shortwave infrared wavelength range using a digital micromirror device and InGaAs linear array detector[J]. Applied optics, 2018, 57(18): 5019-5024.
[9] [9] Land E H. The Retinex theory of color vision[J]. Scientific American, 1978, 237(6): 108-128.
[10] [10] Jobson D J, Rahman Z, Woodell G A. Properties and performance of a center/surround Retinex[J]. IEEE Trans. Image Process., 1997, 6(3): 451-462.
[11] [11] Jobson D J, Rahman, Woodell G A, et al. A multiscale Retinex for bridging the gap between color images and the human observation[J]. IEEE Transactions on Image Process., 1997, 6(7): 965-965.
[12] [12] FU Xueyang, ZENG Delu, YUE Huang, et al. A weighted variational model for simultaneous reflectance and illumination estimation[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016: DOI: 10.1109/CVPR.2016.304.
[13] [13] GUO Xiaojie, YU Li, LING Haibin. LIME: low-light image enhancement via illumination map estimation[J]. IEEE Transactions on Image Processing, 2016, 26(2): 982-993.
[14] [14] REN Xutong, YANG Wenhan, CHENG Wenhuang, et al. LR3M: Robust low-light enhancement via low-rank regularized Retinex model[J]. IEEE Transactions on Image Processing, 2020, 29: 5862-5876.
[15] [15] Pizer S M, Johnston R E, Ericksen J P, et al. Contrast-limited adaptive histogram equalization: Speed and effectiveness[C]//Proc. 1st Conf. Visualizat. Biomed. Comput., 1990: 337-345.
[16] [16] Marques T P, Albu A B. L2UWE: a framework for the efficient enhance-ment of low-light underwater images using local contrast and multi-scale fusion[C]//Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), 2020: 538-547.
[17] [17] HAO Shijie, HAN Xu, GUO Yanrong, et al. Low-light image enhance-ment with semi-decoupled decomposition[J]. IEEE Trans. Multimedia, 2020, 22(12): 3025-3038.
[18] [18] Hautiere N, Tarel J P, Aubert D, et al. Blind contrast enhancement assessment by gradient ratioing at visible edges[J]. Image Analysis & Stereology, 2011, 27(2): 87-95.
[19] [19] WANG Shiqi, MA Kede, Yeganeh H, et al. A patch-structure represent-tation method for quality assessment of contrast changed images[J]. IEEE Signal Processing Letters, 2015, 22(12): 2387-2390.
[20] [20] Matkovic K, Lszl Neumann, Neumann A, et al. Global contrast factor-a new approach to image contrast[C]//Computational Aesthetics 2005: Eurographics Workshop on Computational Aesthetics in Graphics, Visualization and Imaging 2005: 25-33.
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YANG Feng, ZHAO Weijun, GU Yan, DONG Junyuan, LYU Yang, LI Haisheng, GUO Yiliang, ZHU Bo. Low-light Image Enhancement via Detail Saliency Estimation[J]. Infrared Technology, 2024, 46(10): 1145