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视频压缩感知中基于菱形快速搜索的双匹配区域预测 被引量:7

A Prediction Scheme Based on Fast Diamond Search and Two Match Regions in Compressed Video Sensing
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摘要 多假设预测是视频压缩感知多假设预测残差重构算法的关键技术之一,但目前的多假设预测算法对运动剧烈的视频序列依然存在计算复杂度高且质量不佳的缺陷,而且由于观测值与真实信号是一对多的关系,只采用观测值的绝对误差和准则选择假设块容易引入噪声,从而限制了重构质量.针对这些问题,文中结合视频前/后景的运动特征,提出了基于菱形快速搜索的双匹配区域多假设预测算法(MH-DS),即利用菱形快速搜索方式确定当前解码块的前景/后景的运动矢量,获得两个最佳搜索窗,从中搜索多假设匹配块组;在匹配过程中,采用融合最小均方误差和最大匹配像素统计的块匹配准则,以得到更相关的假设块.仿真结果表明,基于菱形快速搜索的双匹配区域多假设算法能够有效地降低重构端多假设预测过程的计算复杂度,与现有最优视频压缩感知预测-重构算法相比,提升了预测精度和重构质量. Multi-hypothesis prediction( MH) is a key technique in compressed video sensing( CVS) predictionresidual reconstruct-algorithm. Unfortunately,when dealing with fast moving sequences,high computational complexity and low prediction accuracy are unavoidable. Besides,MH in measurement domain just employs the sum of absolute difference( SAD) principle to select hypothesis blocks,which usually introduces noise in the prediction blocks and decreases the reconstruction quality for neglecting the one-to-many relationship between the given measurement and original signals. To address these issues,this paper takes advantage of the motion features in video and proposes a multi-hypothesis prediction scheme based on fast diamond search with two matching regions( MHDS). The MH-DS uses the fast diamond search method to search in two different directions for two optimal matching regions,where hypothesis blocks are obtained. MH-DS reduces the computational complexity of the searching process and get more effective prediction information. Moreover,a new matching criterion integrating mean square error( MMSE) with maximum pixels counting( MPC) is proposed in MH-DS in order to get more relevant hypothesis blocks. Simulative results show that the proposed MH-DS reduce the computational complexity of prediction process at reconstruction side and obtain higher prediction accuracy and higher reconstruction quality than the stateof-the-art CVS prediction methods.
作者 杨春玲 戴超 YANG Chunling;DAI Chao(School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510640,Guangdong, China)
出处 《华南理工大学学报(自然科学版)》 EI CAS CSCD 北大核心 2018年第3期49-57,共9页 Journal of South China University of Technology(Natural Science Edition)
基金 国家自然科学基金资助项目(61471173) 广东省自然科学基金资助项目(2016A030313455 2017A030311028)~~
关键词 视频压缩感知 多假设预测 菱形搜索 块匹配准则 compressed video sensing multi-hypothesis prediction diamond search block matching criterion
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