铁路综合视频图像去雾算法研究与探讨

受雾霾等复杂介质环境影响,铁路视频监控系统获得的视频图像降质严重,使得雾霾天图像复原方法研究成为亟待解决的关键性问题。铁路雾霾视频监控图像具有分辨率低、灰度分布集中等主要特点,深入研究分析直方图均衡算法、Retinex图像增强算法和暗通道先验去雾算法的图像处理原理,分析图像处理效果。利用3种算法对铁路室外图像进行分析处理,结果表明3种算法均可以实现去雾,直方图均衡算法存在颜色失真和光晕现象; Retinex图像增强算法清晰度最好,但处理后的图像存在部分失真;暗通道先验去雾算法处理图像较为自然。

Study on the Algorithm for Image Haze Removal in Railway Integrated Video Surveillance System

Affected by the complex medium environment such as fog and haze, the video image obtained by the railway video surveillance system is seriously degraded, which makes it a key issue to restore the degraded images, and the study on restoration method very urgent. This paper discusses the main features such as low-resolution and gray-scale distribution of the railway video surveillance image in haze day, analyses the image processing principle and the effects of the three algorithms, i. e., histogram equalization, Retinex improvement for image enhancement, and image haze removal using dark channel prior. Outdoor images of the railway are processed by the three algorithms, and the results show that all the three algorithms are effective in haze removal. Histogram equalization features color distortion and halo. Though the enhanced images using Retinex improvement have the best resolution, they are partially distorted. The images processed by haze removal using dark channel prior are more natural.