Fusion-based simultaneous estimation of reflectance and illumination for low-light image enhancement

Abstract

Low-light image enhancement is a challenging field in image processing. Retinex-based methods perform well for low-light images. However, reflectance and illumination estimation is an ill-posed problem. This paper presents a new framework for the simultaneous estimation of reflectance and illumination for low-light image enhancement. The algorithm estimates multiple instances of illumination and reflectance and blends them to estimate the final components. The proposed approach uses multi-scale fusion for illumination estimation and naive fusion for reflectance estimation. Extensive experimentation and analysis with a large set of low-light images validates the performance of the proposed approach. The comparison shows the superiority of the proposed approach over most of the existing low-light image enhancement methods. The proposed method provides colour constancy in low-light image enhancement and preserves the naturalness of the image.