低光照图像的亮度增强与颜色恢复方法研究  

Research on Brightness Enhancement and Color Restoration of Low-light Images

作　　者：曹颖川 黄磊 宋子硕 郭辉 CAO Yingchuan;HUANG Lei;SONG Zishuo;GUO Hui(School of Information Engineering,Ningxia University,Yinchuan 750021)

机构地区：[1]宁夏大学信息工程学院,银川750021

出　　处：《计算机与数字工程》2023年第8期1839-1843,1855,共6页Computer & Digital Engineering

基　　金：宁夏自然科学基金项目(编号:2021AAC03117)资助。

摘　　要：低光照图像由于能见度低,不利于人眼观察和计算机视觉处理中的目标特征识别。为此,论文提出了一种基于同态滤波与颜色恢复相结合的低光照图像增强方法。首先,采用同态滤波对低光图像进行初步处理,增强图像的亮度和纹理;其次,在Lab颜色空间下,对a、b颜色通道进行偏色分析,并基于直方图规定化对经过同态滤波处理的图像的a、b颜色通道进行色彩匹配校正;最后,将三通道合并转换到RGB颜色空间,得到最终的增强图像。实验表明,该图像增强方法对低光照图像的亮度增强和颜色恢复具有较好的性能,且更符合人眼视觉。Low light images are not conducive to human eye observation and target feature recognition in computer vision processing due to low visibility.Therefore,this article proposes a low light image enhancement method based on a combination of homomorphic filtering and color restoration.Firstly,homomorphic filtering is used for preliminary processing of low light images to enhance their brightness and texture.Secondly,in the Lab color space,color deviation analysis is performed on the a and b color channels,and color matching correction is performed on the a and b color channels of the image processed by homomorphic filtering based on histogram normalization.Finally,merge and transform the three channels into the RGB color space to obtain the final enhanced image.Experiments have shown that this image enhancement method has good performance in brightness enhancement and color restoration of low light images and is more in line with human vision.

关 键 词：低光照图像增强 同态滤波 Lab颜色空间 直方图规定化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]