一种低照度煤矿井下图像增强算法  

A Low-Illumination Coal Mine Underground Image Enhancement Algorithm

作　　者：苏畅[1] 王松[1] Su Chang;Wang Song(School of Mechanical Engineering,Anhui University of Science and Technology,Huainan,Anhui 232001,China)

机构地区：[1]安徽理工大学机电工程学院,安徽淮南232001

出　　处：《黑龙江工业学院学报(综合版)》2024年第10期87-90,共4页Journal of Heilongjiang University of Technology(Comprehensive Edition)

基　　金：国家自然科学基金资助项目(项目编号:52374156)。

摘　　要：煤矿井下的安全监控是开采过程中重要的一部分,井下光照不均匀、对比度低,存在大量粉尘和喷雾降尘的水雾,严重影响了井下图像的清晰度。针对这一问题,提出一种低照度煤矿井下图像增强算法。首先,对原始图像采用改进的同态滤波进行处理;其次,将图像从RGB空间转换为HSV空间,对亮度分量V进行融合S型曲线的CLAHE增强;最后,将图像从HSV空间转回到RGB空间中,用完美反射法来校正颜色偏移。将该算法与改进前后同态滤波算法、改进前后CLAHE算法进行了对比试验,实验结果显示:该算法能改善矿井下光照不均匀的影响,增强暗区域细节信息,在图像的信息熵和均值上有很高的提升。Coal mine safety monitoring is an important part of the mining process,underground lighting is uneven,low contrast,there is a large amount of dust and spray dust water mist,seriously affecting the clarity of underground images.In order to solve this problem,this paper proposes a low-illumination coal mine image enhancement algorithm.Firstly,the original image is processed by improved homomorphic filtering,then the image is converted from RGB space to HSV space,the luminance component V is fused with the CLAH enhancement of the S-curve,and finally the image is transferred from HSV space back to RGB space,and the perfect reflection method is used to correct the color shift.The proposed algorithm is compared with the improved before and after homomorphic filtering algorithm and the improved before and after CLYE algorithm.The experimental results show that the algorithm can improve the influence of uneven illumination in the mine,enhance the detail information of the dark area,and improve the information entropy and mean value of the image.

关 键 词：图像增强 低照度 煤矿井下图像 同态滤波 S型曲线 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]