Visual data deblocking using structural layer priors

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.

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LIME: Low-Light Image Enhancement via Illumination Map Estimation

Guo

Ling

2017

IEEE Trans. on Image Process.

1,984

1,400

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Visual data deblocking using structural layer priors

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Cited by 1 publication

References 24 publications

LIME: Low-Light Image Enhancement via Illumination Map Estimation

LIME: Low-Light Image Enhancement via Illumination Map Estimation

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