基于图像增强的去雾算法研究

Research on the Defogging Algorithm Based on Image Enhancement

在"地摊经济"下的城市环境智能监测系统的搭建过程中,文章针对户外摄像头在雾天、雪天、雨天或雾霾等影响下,获取的图像会出现模糊、过暗或细节丢失等现象进行了研究。对比了基于图像增强的全局直方图均衡化、局部直方图均衡化、单尺度Retinex算法、多尺度加权平均Retinex算法以及带色彩恢复的多尺度Retinex算法的图像去雾原理和仿真结果。引入多种客观评估指标,构建了主客观评价和客观评估相结合的图像去雾效果评价方法。

In the process of building an intelligent monitoring system for urban environment under the"stall economy",this paper studies the phenomenon that the images obtained by outdoor cameras will appear blurred,too dark or details lost under the influence of fog,snow,rain or haze.The principles and simulation results of global histogram equalization,local histogram equalization,single scale Retinex algorithm,multi-scale weighted average Retinex algorithm and multi-scale Retinex algorithm with color restoration are compared.By introducing a variety of objective evaluation indexes,an image defogging effect evaluation method combining subjective and objective evaluation is constructed.