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LIME: Low-Light Image Enhancement via Illumination Map Estimation.

Authors :
Xiaojie Guo
Yu Li
Haibin Ling
Source :
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society [IEEE Trans Image Process] 2017 Feb; Vol. 26 (2), pp. 982-993. Date of Electronic Publication: 2016 Dec 14.
Publication Year :
2017

Abstract

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.

Details

Language :
English
ISSN :
1941-0042
Volume :
26
Issue :
2
Database :
MEDLINE
Journal :
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Publication Type :
Academic Journal
Accession number :
28113318
Full Text :
https://doi.org/10.1109/TIP.2016.2639450