基于Retinex和Gamma变换的低照度图像增强方法  

Low-illumination Image Enhancement Method Based on Retinex and Gamma Transformation

作　　者：王文韫 舒晨洋 朱龙涛 黄靖龙 杨景云 李寿科 WANG Wenyun;SHU Chenyang;ZHU Longtao;HANG Jingong;YANG Jingyun;LI Shouke(Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment,Hunan University of Science and Technology,Xiangtan 411201,China;College of Civil Engineering,Hunan University,Changsha 410082,China)

机构地区：[1]湖南科技大学机械设备健康维护湖南省重点实验室,湖南湘潭411201 [2]湖南大学土木工程学院,湖南长沙410082

出　　处：《湖南大学学报（自然科学版）》2024年第10期136-144,共9页Journal of Hunan University:Natural Sciences

基　　金：湖南省自然科学基金资助项目(2023JJ50234,2021JJ50008);湖南省教育厅科学研究项目(22B0465,20A179);湖南省重点研发计划项目(2021GK2005)。

摘　　要：为均衡增强低照度图像的同时,保留其更多的细节信息,提出一种改进Retinex低照度图像增强算法.该算法基于HSV(Hue,Saturation,Value)颜色空间,对分离出的明度分量和饱和度分量进行增强.首先,使用限制对比度自适应直方图均衡化(Contrast Limited Adap-tive Histogram Equalization,CLAHE)优化明度分量,使图像更接近均匀光照场景,并使用自适应Gamma对饱和度分量进行校正.然后,采用三维块匹配滤波(Block-matching and 3D Filter-ing,BM3D)算法对光照分量进行估计,并求得相应的反射分量,提出一种改进Gamma变换函数,依据光照分量信息对明度分量进行增强,同时,采用Gabor滤波器和Canny算法对原图进行细节提取,提出一种细节增强策略,对反射分量及其纹理细节进行增强.最后,将各分量进行加权融合,再将增强图像变换回RGB空间.实验结果表明,所提算法相较于自动色彩均衡、自适应局部色调映射、低光照图像增强、带色彩恢复多尺度视网膜增强算法有更好的增强效果和普适性,且原图经过增强后,信息熵、峰值信噪比、结构相似性指数、图像质量指数、平均梯度有显著提升,均方根误差显著下降.An improved Retinex low-illumination image enhancement algorithm is proposed for the balanced enhancement of low-illumination images while retaining their more detailed information.The algorithm is based on the HSV(Hue,Saturation,Value)color space and enhances the separated luminance and saturation components.First,the brightness component is optimized using Contrast Limited Adaptive Histogram Equalization(CLAHE)to make the image closer to the uniformly illuminated scene,and the saturation component is corrected using Adaptive Gamma.Then,a Block-matching and 3D Filtering(BM3D)algorithm is used to estimate the illumination component,the corresponding reflection component is obtained,and an improved Gamma transform function is proposed to enhance the luminance component based on the information of the illumination component.Meanwhile,the Gabor filter and Canny algorithm are used to extract the details of the original image,and a detail enhancement strategy is proposed to enhance the reflection component and its texture details.Finally,the components are fused with multiple weights,and then the enhanced image is transformed back to RGB space.Experimental results show that the proposed algorithm has better enhancement effect and universality than automatic color equalization,adaptive local tone mapping,low-illumination image enhancement,and multi-scale Retinex with color restoration.After enhancement,the original image showed significant improvements in information entropy,peak signal-to noise ratio,structural similarity index,universal image quality index,average gradient,while the root mean square error decreased significantly.

关 键 词：图像增强 低照度图像 改进Retinex算法 BM3D算法 GABOR滤波 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]