Low-light image enhancement based on Retinex decomposition and adaptive gamma correction

Abstract

Low-light images suffer from poor visibility and noise. In this paper, a low-light image enhancement method based on Retinex decomposition is proposed. A pyramid network is first utilized to extract multi-scale features to improve the quality of Retinex decomposition. Then the decomposed illumination is refined via an adaptive Gamma correction network to handle non-uniform illumination, while the decomposed reflectance is refined with a lightweight network. Finally, the enhanced image is obtained by element-wise multiplication between the refined illumination and reflectance components. Quantitative and qualitative experiments demonstrate the superiority of our method over state-of-the-art image enhancement methods.