NSDIE: Noise Suppressing Dark Image Enhancement Using Multiscale Retinex and Low-Rank Minimization

Abstract

It is inevitable for dark images to have crucial information obscured by low-light conditions, which are worsened by the presence of noise in these images. This work introduces a groundbreaking solution, Noise-Suppressing Dark Image Enhancement for Web Apps (NSDIE), to address the challenging task of enhancing low-light images marred by noise. The proposed work utilizes a low-rank model with simultaneous enhancement of reflectance and illumination components to improve the nighttime scenes while also eradicating the present noise of the image. The reflectance component is further processed using a multiscale retinex model to compensate for the possible color distortions while the illumination component is enhanced using the camera response model to ensure the genuineness of the scene. The proposed work is also tested for a standalone application and is presented to the user through a web portal to aid the concerns of dark image enhancement in the daily life of the user. Rigorous quantitative and qualitative analyses assert NSDIE's superiority over existing techniques, establishing its pivotal role in addressing the critical concern of dark image enhancement.