“LIME: Low-Light Image Enhancement via Illumination Map Estimation” (2016), by Xiaojie Guo et al. Computer Science research paper. Original abstract below, unchanged. No free PDF was found.

LIME: Low-Light Image Enhancement via Illumination Map Estimation

Xiaojie Guo, Yu Li, Haibin Ling · December 14, 2016 · Computer Science

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.

Source page DOI: 10.1109/tip.2016.2639450