信息与控制2024，Vol.53Issue(5)：652-661,672,11.DOI:10.13976/j.cnki.xk.2024.3305
基于多通道Retinex模型的低照度图像增强网络
Low-light Image Enhancement Network Based on Multichannel Retinex Model
摘要
Abstract
Low-light image enhancement has been one of the hottest research fields of computer vision in recent years.It has many applications in object detection,autonomous driving,and night monito-ring.The pixel value distribution of images obtained from the same scene is analyzed under different exposures.It finds differences in the growth ratio of its low-light and normal-illumination images in RGB three channels.Based on this observation,a low-light image enhancement network is proposed on the basis of multi-channel Retinex model.In order to solve the problem of color de-viation after low-light enhancement,a multi-channel enhancement strategy is adopted in the light enhancement module,and a targeted color loss function is designed,which improves the quality of generated pictures through the antagonistic loss function.Experimental results show that the peak signal-to-noise ratio between the enhanced image and the reference image is improved by 20％by the proposed method in comparison with the existing advanced algorithms through experiments on two public datasets,and structural similarity is improved by 7.2％.The noise of image is elimina-ted,and it is closer to the reference image in terms of numerical indicators and visual effects.关键词
低照度图像增强/光照分解/Retinex 模型Key words
low-light image enhancement/illumination decomposition/Retinex model分类
信息技术与安全科学引用本文复制引用
张箴,鹿阳,苏奕铭,唐延东,田建东..基于多通道Retinex模型的低照度图像增强网络[J].信息与控制,2024,53(5):652-661,672,11.基金项目
国家自然科学基金(U2013210) （U2013210）
