融合视觉特性的交通视频雾霾去除方法研究

项目名称： 融合视觉特性的交通视频雾霾去除方法研究

项目编号： No.61471166

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 无线电电子学、电信技术

项目作者： 凌志刚

作者单位： 湖南大学

项目金额： 80万元

中文摘要： 智能交通视频监控系统已经在智能交通中得到广泛的应用，然而近年频繁发生的雾霾天气导致监控视频质量降低，严重制约和影响了视频监控系统正常有效的工作，交通低质视频雾霾去除成为了智能视频监控系统迫切需要解决的问题。因此，本课题系统地研究面向智能交通监控的低质视频雾霾去除方法。研究建立昼夜不同时刻的大气散射物理模型以及噪声抑制策略；分析雾霾图像特征及统计规律，研究昼间雾霾天气自动识别方法；从图像复原与图像增强两个角度分别研究昼夜不同时段的雾霾去除与噪声抑制方法；为提高雾霾去除质量，融合人眼视觉特性，研究最大化图像增强的雾霾去除与宽动态范围图像增强方法；进而，研究基于时空双边滤波的视频雾霾去除方法，最终形成一套适合交通视频监控系统的雾霾去除与增强新方法。

中文关键词： 低质视频；雾霾去除；退化模型；图像增强；人类视觉特性

英文摘要： Intelligent surveillance system has been widely used in intelligent transportation system, however, fog and haze, especially in recent years, often degrade the video quality, and severely restrict the performance of intelligent surveillance systems, The fog and haze removal for low-quality traffic video has become a problem that calls for immediate solution in intelligent traffic surveillance systems. Therefore, this project will systematically study the fog or haze removal and enhancement method for the low quality videos of traffic surveillance system. Firstly, this project will analyze and build the image degradation model in the daytime and nighttime haze weather, respectively. By analyzing the characteristics and statistical laws of these foggy and hazed images, this project will develop a daytime-haze automatic identification method. Then, from the point of image restoration and enhancement views, this project will develop several image dehazing and wide dynamic range image enhancement methods for daytime and nighttime images by integrating human visual characteristics and maximizing the quality of restored images. Furthermore, a low-quality video dehazing method based on the bilateral temporal-spatial filter will be proposed. Lastly, a new video haze removal and enhancement method will be proposed to improve the low-quality traffic surveillance video.

英文关键词： low-quality video;fog and haze removal;degradation model;image enhancement;human visual characteristic