Low⁃light image enhancement algorithm based on dual branch channel prior and Retinex

被引：0

作者：

Li, Yang ^{[1
,2
,3
]}

Li, Xian-Guo ^{[1
,3
]}

Miao, Chang-Yun ^{[1
,3
]}

Xu, Sheng ^{[2
]}

机构：

[1] School of Electronics and Information Engineering, Tiangong University, Tianjin

[2] School of Software and Communications, Tianjin Sino-German University of Applied Sciences, Tianjin

[3] Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, Tianjin

来源：

Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2025年 / 55卷 / 03期

关键词：

channel prior features; dual-branch channel retinexnet; image enhancement; low light image; pixel hybrid attention mechanism;

D O I：

10.13229/j.cnki.jdxbgxb.20240148

中图分类号：

学科分类号：

摘要：

A low illumination image enhancement algorithm based on dual branch channel priors and Retinex is proposed to address the issues of local dimming，detail loss，and over enhancement in existing algorithms. Firstly，on the basis of Retinex，a dual branch bright dark prior feature guidance method is proposed，and a bright channel prior feature module and a dark channel prior feature module are designed to guide the network to suppress reflection component noise and improve lighting component brightness；Secondly，a pixel mixed attention mechanism module is designed to learn targeted features from three dimensions：channel，space，and pixel；Thirdly，a dark channel refractive index estimation module is designed to amplify image detail features. Finally，a mixed loss function is used to adjust brightness，contrast，noise，and color constraints. The experimental results on public datasets show that compared with 10 advanced algorithms，this algorithm improves image brightness while reducing color distortion and detail loss，achieving the best visual effects and quality indicators. © 2025 Editorial Board of Jilin University. All rights reserved.

引用

页码：1028 / 1036

页数：8

共 28 条

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