Low-light Enhancement Using Retinex-Decomposition Convolutional Neural Networks

Abstract

This paper proposes a new retinex-decomposition convolutional network (DC-Net) to enhance low-light images based on retinex theory. The proposed method estimates the reflectance and illumination components using Dc-Net. Bright-Net and Smooth-Net are used for the refined illumination, and Denoise-Net returns the noise-removed reflectance. Finally, A resultant image can be estimated by multiplying the noise-removed reflectance map and brightness-improved illumination. The experimental results show that the proposed scheme can provide high-quality images without saturation. © 2022 IEEE.