Papers › LIME: Low-light Image Enhancement via Illumination Map Estimation

LIME: Low-light Image Enhancement via Illumination Map Estimation

3 Dec 2016IEEE TIP 2016 12archive 2025-07-28

Xiaojie Guo, Yu Li, Haibin Ling

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 highquality 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. Further, 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.

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Tasks

Image EnhancementLow-Light Image Enhancement

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Low-Light Image Enhancement 10 Monkey Species Cat 10 way 1~2 shot 25 #1 of 1 Archive leaderboard report

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Methods

LIME

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