LIME: Low-Light Image Enhancement via Illumination Map Estimation

被引:1609
|
作者
Guo, Xiaojie [1 ]
Li, Yu [2 ]
Ling, Haibin [3 ]
机构
[1] Chinese Acad Sci, Inst Informat Engn, State Key Lab Informat Secur, Beijing 100093, Peoples R China
[2] Adv Digital Sci Ctr, Singapore 138632, Singapore
[3] Temple Univ, Dept Comp & Informat Sci, Philadelphia, PA 19122 USA
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
Illumination estimation; illumination (light) transmission; low-light image enhancement; HISTOGRAM EQUALIZATION;
D O I
10.1109/TIP.2016.2639450
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
When one captures images in low-light conditions, the images often suffer from low visibility. Besides degrading the visual aesthetics of images, this poor quality may also significantly degenerate the performance of many computer vision and multimedia algorithms that are primarily designed for high-quality inputs. In this paper, we propose a simple yet effective low-light image enhancement (LIME) method. More concretely, the illumination of each pixel is first estimated individually by finding the maximum value in R, G, and B channels. Furthermore, we refine the initial illumination map by imposing a structure prior on it, as the final illumination map. Having the well-constructed illumination map, the enhancement can be achieved accordingly. Experiments on a number of challenging low-light images are present to reveal the efficacy of our LIME and show its superiority over several state-of-the-arts in terms of enhancement quality and efficiency.
引用
收藏
页码:982 / 993
页数:12
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