Effective enhancement method of low-light-level images based on the guided filter and multi-scale fusion

Abstract

Aiming to solve the problem of low-light-level (LLL) images with dim overall brightness, uneven gray distribution, and low contrast, in this paper, we propose an effective LLL image enhancement method based on the guided filter and multi-scale fusion for contrast enhancement and detail preservation. First, a base image and detail image(s) are obtained by using the guided filter. After this procedure, the base image is processed by a maximum entropy-based Gamma correction to stretch the gray level distribution. Unlike the existing methods, we enhance the detail image(s) based on the guided filter kernel, which reflects the image area information. Finally, a new method is proposed to generate a sequence of artificial images to adjust the brightness of the output, which has a better performance in image detail preservation compared with other single-input algorithms. Experiments show that the proposed method can provide a more significant performance in enhancing contrast, preserving details, and maintaining the natural feeling of the image than the state of the art.