基于低照度的有雾彩色图像增强算法  

Low-Illumination-Based Enhancement Algorithm of Color Images with Fog

作　　者：仲伟峰[1] 袁东雪 Zhong Weifeng;Yuan Dongxue(School of Automation,Harbin University of Science and Technology,Harbin,Heilongjiang 150080,China)

机构地区：[1]哈尔滨理工大学自动化学院,黑龙江哈尔滨,150080

出　　处：《激光与光电子学进展》2020年第16期215-221,共7页Laser & Optoelectronics Progress

摘　　要：针对Retinex算法在去雾时会出现光照不均匀、彩色失真等情况,提出了一种基于低照度的有雾彩色图像增强算法。该算法首先将红-绿-蓝(RGB)图像转换到色调-饱和度-亮度(HSV)空间区域,对亮度(V)分量进行提取,将单尺度Retinex算法作用于V分量后对V分量进行伽马校正;将MSRCR算法中的高斯滤波器改为引导滤波并进行低通滤波;最后将改进的SSR算法、MSRCR算法、基于拉普拉斯金字塔的Retinex算法得到的图像进行加权融合。该算法能够得到很好的去雾效果,有效地抑制光晕并改善色彩失真等问题。经所提算法处理后,图片的相似性、信息熵等指标均得到了提升。To solve the problem of uneven illumination and color distortion in the Retinex algorithm for defogging,we propose an enhancement algorithm of color images with fog based on low illumination.First,this algorithm converts the red-green-blue(RGB)image into the hue-saturation-value(HSV)spatial region,extracts the value(V)component,and performs Gamma correction for the V component after the single-scale Retinex algorithm is applied to the V component.Then,the Gaussian filter in the MSRCR algorithm is changed into guided filtering and the low-pass filtering is performed.Finally,the images obtained by the improved SSR algorithm,the MSRCR algorithm,and the Retinex algorithm based on the Laplace pyramid are weighted and fused.The proposed algorithm can get a good effect in fog removal and can effectively suppress halo and improve color distortion.As for those images processed by the proposed algorithm,the image similarity,information entropy and other indicators have been improved.

关 键 词：图像处理 图像增强 有雾图像 RETINEX算法 加权融合 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]