DSE-Net: Deep simultaneous estimation network for low-light image enhancement

This paper presents a novel approach for low-light image enhancement. We propose a deep simultaneous estimation network (DSE-Net), which simultaneously estimates the reflectance and illumination for low-light image enhancement. The proposed network contains three modules: image decomposition, illumination adjustment, and image refinement module. The DSE-Net uses a novel branched encoder-decoder based image decomposition module for simultaneous estimation. The proposed decomposition module uses a separate decoder to estimate illumination and reflectance. DSE-Net improves the estimated illumination using the illumination adjustment module and feeds it to the proposed refinement module. The image refinement module aims to produce sharp and natural-looking output. Extensive experiments conducted on a range of low-light images demonstrate the efficacy of the proposed model and show its supremacy over various state-of-the-art alternatives.