一种新的基于分块的视频压缩感知算法  

A Novel Block-Based Algorithm for Compressive Video Sensing

作　　者：李涛[1] 王晓华[1] 赵三元[2] 

机构地区：[1]北京理工大学信息与电子学院,北京100081 [2]北京理工大学计算机学院,北京100081

出　　处：《北京理工大学学报》2013年第9期940-944,共5页Transactions of Beijing Institute of Technology

基　　金：北京理工大学基础研究基金资助项目(3050012211105)

摘　　要：提出了一种新的基于分块的视频压缩感知算法,可以将视频采集和压缩编码有机结合起来同时进行.为利用视频时间轴上的冗余,对参考帧和非参考帧使用不同的采样策略:对于参考帧,先进行分块然后进行常规的压缩感知采样;对于非参考帧,将分块后和参考帧对应块作比较然后调整采样策略.非参考帧的采样可以为参考帧提供更多的信息,使得在采样数目很少的情况下得到更高的视频质量.同时算法可以根据视频帧内部的纹理复杂程度自适应地调整采样速率,优化资源配置.实验结果表明,相对于一般的压缩采样算法,本算法使用比以往算法少20%以上的采样值,得到的结果既符合人眼观察又有最高的信噪比.Proposed a block-based compressive video sensing algorithm,which allows to pursue video acquisition and video compressed coding synchronously. To explore the temporal redundancy of the video, different sensing strategies were used between reference frames and non-reference frames, for reference frames, the frames were divided to little patches and employed regular compressive sensing to every patch; while for the rest ones, first the frams were divided into blocks in the same size and then compared the blocks with the corresponding block in reference frame, pursue different sensing method according to the results. The frame quality is better because non-reference frame observation could feedback the reference frames. Meanwhile,the sampling rate changes adaptively according to the texture complication. The experimental results with 20% less samples than other methods indicate that the algorithm is more suitable to human eyes and also gets higher PSNR.

关 键 词：压缩感知 分块 信噪比 自适应 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]