Low-light image enhancement using multi-layer fusion and detail recover

Qiaosong Chen; Pei Xu; Wenshan Yan; Shangsheng Feng; Xin Deng; Jin Wang

doi:10.1117/12.2502833

9 August 2018 Low-light image enhancement using multi-layer fusion and detail recover

Qiaosong Chen, Pei Xu, Wenshan Yan, Shangsheng Feng, Xin Deng, Jin Wang

Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 1080628 (2018) https://doi.org/10.1117/12.2502833
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China

Abstract

Due to contrast deficiency and blurred details in some low-light images, this paper presents a low-light image enhancement method using multi-layer fusion and detail recovery. Firstly, V channel in HSV color space is copied to three layers: Retinex layer, brightness layer and detail layer. In Retinex layer, the combination of weighted guided image filtering and morphology eliminates halo phenomenon. Meanwhile brightness and details of images are enhanced by the improved Retinex. Adaptive normalization is adopted to enhance brightness further in brightness layer. In detail layer, the improved model of local linear is to obtain more details. Finally, a detail recovery based on pixel arrangement is performed to avoid partial fuzzy details caused fusion. Experimental results show that the proposed method can more effectively highlight image details and improve the contrast.

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Qiaosong Chen, Pei Xu, Wenshan Yan, Shangsheng Feng, Xin Deng, and Jin Wang "Low-light image enhancement using multi-layer fusion and detail recover", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 1080628 (9 August 2018); https://doi.org/10.1117/12.2502833

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KEYWORDS

Image enhancement

Image fusion

Image filtering

Visualization

Distortion

Control systems

Image processing

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