Low-light image enhancement algorithm based on Retinex

Abstract

The goal of the low-light picture enhancement challenge is to increase an image's visibility without sacrificing its visually authentic appearance. This study addresses the issues of uneven brightness and negligible features in low-light photographs by proposing an enhanced Retinex algorithm for low-light image improvement. The RGB image is first converted to an HSV color space, and the multi-scale Retinex (MSR) algorithm is then applied to the V channel (brightness channel). This algorithm replaces the Gaussian filter in the Retinex algorithm with an adaptive bilateral filter and a Gabor filter, combining the qualities of the two filters to improve the image's brightness and details; Then, the original image is sharpened to improve the details of the image; Finally, the enhanced image is weighted and fused with the sharpened image to avoid the loss of details in the dark or overexposed regions of the image. The methods described in this paper are significantly improved compared with the classic Multi-Scale Retinex (MSR) algorithm and Multi-Scale Retinex with Color Restore (MSRCR) algorithm, which are able to repair the appearance of the image while maintaining its color and edges. color and edges while restoring the look and feel of the image.