雾霾天气条件下监控视频的复原与增强研究

项目名称： 雾霾天气条件下监控视频的复原与增强研究

项目编号： No.61471272

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： 肖进胜

作者单位： 武汉大学

项目金额： 83万元

中文摘要： 雾霾天气、光照变化和噪声是户外监控视频技术发展和应用的主要障碍。本项目将致力于修正和完善雾霾天气下监控视频复原与增强的理论和方法。深入研究成像设备的噪声模型、雾霾视频退化的物理模型和光学成像的点扩散模型，建立能够准确描述雾霾天气下降质监控视频的统一退化模型。充分利用监控视频的结构自相似性和稀疏性等先验知识，按照各处理环节的重点和信号特点，通过数据分类、变换滤波等先进技术，提取视频中感兴趣的成分，根据光学成像原理和人眼视觉感知特性，抑制噪声和雾霾，增强色彩和纹理，改善监控视频质量。具体研究：基于成像设备噪声模型的视频去噪方法，基于修正物理成像模型的视频去雾霾方法，基于光照不变性和视觉感知特性的视频增强方法。利用仿真和实验验证所提户外监控视频复原与增强方法，实现全天候高分辨率外场成像。本项目研究结果将极大改善监控视频质量，并促进监控视频在智能交通和安全防范等领域中的应用。

中文关键词： 图像处理；退化模型；图像去噪；图像复原；图像增强

英文摘要： The foggy and hazy weather, illumination changes and noise are the main obstacles in the technological developments and applications of outdoor surveillance video. This project focuses on improving the theories and methods of the restoration and enhancement of surveillance video under hazy weather conditions. It is devoted to the studies of the noise model of imaging devices, the physical model of hazy video, and point spread model of optical imaging to establish a general degradation model. This general model can accurately describe the quality of surveillance video degraded by hazy weather conditions. According to key points of each processing link and signal characteristics, this project will explore the structural self-similarities, the sparsities and other prior knowledge of surveillance video. Several advanced techniques will be used to extract the component of interest from surveillance video, which include data classification, transform filtering and so on. The interesting component will be attenuated or enhanced to improve the surveillance video quality based on both the optical imaging principle and the human visual perception features. This project focuses on the studies of video denoising based on the noise model of imaging devices, video dehazing based on the optimized physical model, and video enhancement based on both illumination invariance and human visual perception characteristics. This task is also devoted to how to use the numerical simulation and experiments to validate the proposed methods. The validation indicates that the proposed method can successfully increase the surveillance video quality of outdoor high-resolution imaging in all weather conditions. This project tackles the key problems in surveillance video processing technology, and the results can greatly promote the applications of surveillance video in the intelligent transportation and security systems.

英文关键词： Image processing;Degradation model;Image denoising;Image restoration;Image enhancement