一种煤矿井下低照度图像增强算法  

An enhancement algorithm for low-illumination image of underground coal mine

作　　者：王洪栋 郭伟东 朱美强 雷萌 WANG Hongdong;GUO Weidong;ZHU Meiqiang;LEI Meng(School of Information and Control Engineering,China University of Mining and Technology,Xuzhou 221116,China)

机构地区：[1]中国矿业大学信息与控制工程学院

出　　处：《工矿自动化》2019年第11期81-85,共5页Journal Of Mine Automation

基　　金：国家自然科学基金资助项目(61901003,51904297);中国博士后基金资助项目(2014M551695)

摘　　要：针对多尺度Retinex算法在处理煤矿井下低照度图像时存在细节增强不足和耗时等问题,提出了一种基于光照校正的快速多尺度Retinex算法对煤矿井下低照度图像进行增强。该算法通过计算高斯模糊后图像的每个像素点的亮度值,将图像划分为暗调区域和高光区域,并对不同区域进行光照校正,从而降低高光区域的亮度,保证不过分曝光,同时提升较暗区域的亮度,凸显更多细节信息;利用三次快速均值滤波代替高斯滤波来估计光照强度,减少算法耗时。实验结果表明,该算法能有效提高图像的亮度和对比度,增强图像中暗调区域和高光区域的细节,具有较快的处理速度。The multi-scale Retinex algorithm has some problems such as insufficient detail enhancement and long time-consumption in processing low-illumination image of underground coal mine.Aiming at the problem,a fast multi-scale Retinex algorithm based on illumination correction was proposed to enhance low-illumination image of underground coal mine.By calculating brightness value of each pixel of image after gaussian blur,the image is divided into dark and highlight areas,and illumination correction is carried out on dark and highlight areas,so as to reduce brightness of highlight area to avoid overexposure,and improve brightness of dark area to highlight more details.Three-times fast mean filtering is used instead of Gaussian filtering to estimate illumination intensity,so as to reduce time-consumption of the algorithm.The experimental results show that the algorithm can effectively improve brightness and contrast of image,enhance details of dark and highlight areas in image,and has fast processing speed.

关 键 词：矿井图像 低照度图像 图像增强 多尺度RETINEX算法 光照校正 快速均值滤波 

分 类 号：TD67[矿业工程—矿山机电]