计算资源受限条件下的监控视频编码与重建方法研究

项目名称： 计算资源受限条件下的监控视频编码与重建方法研究

项目编号： No.61201268

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 电子学与信息系统

项目作者： 周城

作者单位： 中南民族大学

项目金额： 25万元

中文摘要： 高清智能视频监控是未来安防领域的重要发展方向，其低复杂度编码与高清晰度重建是有待解决的热点问题。监控前端的计算资源受到严格限制，往往采用对原编码标准特性大量裁剪的方法控制计算复杂度，加上监控光照条件复杂恶劣，导致重建视频质量下降，无法满足安防业务需求。本项目将编码计算资源消耗和解码重建质量作为整体研究，提出基于编码统计特性与稀疏表示理论的高效视频编码与超分辨率重建方法，主要研究内容与创新之处包括：1)在编码端通过构建基本编码单元的编码模式开销观测模型，建立混合概率分布判决准则，以极低计算代价优化整体编码流程，降低资源需求，保证重建视频质量；2)在解码端突破传统超分辨率空域重建框架，引入稀疏表达模型，直接在变换域中对因变换量化损失的高频系数进行补偿，最终解算出高分辨率图像。本项目力争取得具有原创性的研究成果，有效解决计算资源开销与视频重建质量之间的矛盾，提高我国安防领域的基础研究水平。

中文关键词： 视频编码；视频监控；计算资源受限；稀疏表示；

英文摘要： High definition intelligence video surveillance defined the important future direction of the security monitoring field, and its low complexity coding and super resolution reconstruction are the hot spot of the problem to be solved. The computing resource of front monitor is very limited, which often led to the huge cutting out of the original coding standard features. And the illumination condition of front monitor is also very bad and complex. All of that will lead to the distortion of the reconstruction video quality and can not satisfy the needs of security business. This project will analyze the coding computing resources consumption problem and decoding reconstruction problem as a whole, and will proposal the video coding method based on statistical properties and the super-resolution reconstruction method based on sparse coding theory. The main research contents and innovative points include: 1) we will build the coding mode cost measurement model of the basic coding unit in the encoder, and establish the mixed probability distribution judgment criterion to optimize the whole encoding process with extremely low computational cost and reduce resource needs as well as ensure video quality of reconstruction; 2) we will break the traditional special framework of super-resolution reconstruction in decoder, and

英文关键词： video coding；video surveillance；computing-resource-constrained；sparse-representation；