A High-Quality Adaptive Video Reconstruction Optimization Method Based on Compressed Sensing  

作　　者：Yanjun Zhang Yongqiang He Jingbo Zhang Yaru Zhao Zhihua Cui Wensheng Zhang 

机构地区：[1]School of Computer Science and Technology,Taiyuan University of Science and Technology,Taiyuan,030024,China [2]Department of Big Data and Intelligent Engineering,Shanxi Institute of Technology,Yangquan,045000,China [3]School of Computer Science,Beijing University of Technology,Beijing,100124,China [4]The Institute of Automation,Chinese Academy of Sciences(CAS),Beijing,100049,China

出　　处：《Computer Modeling in Engineering & Sciences》2023年第10期363-383,共21页工程与科学中的计算机建模（英文）

基　　金：supported by the National Natural Science Foundation of China under Grant No.61806138;KeyR&DProgram of Shanxi Province(International Cooperation)under Grant No.201903D421048;National Key Research and Development Program of China under Grant No.2018YFC1604000;School Level Postgraduate Education Innovation Projects under Grant No.XCX212082.

摘　　要：The video compression sensing method based onmulti hypothesis has attracted extensive attention in the research of video codec with limited resources.However,the formation of high-quality prediction blocks in the multi hypothesis prediction stage is a challenging task.To resolve this problem,this paper constructs a novel compressed sensing-based high-quality adaptive video reconstruction optimizationmethod.Itmainly includes the optimization of prediction blocks(OPBS),the selection of searchwindows and the use of neighborhood information.Specifically,the OPBS consists of two parts:the selection of blocks and the optimization of prediction blocks.We combine the high-quality optimization reconstruction of foreground block with the residual reconstruction of the background block to improve the overall reconstruction effect of the video sequence.In addition,most of the existing methods based on predictive residual reconstruction ignore the impact of search windows and reference frames on performance.Therefore,Block-level search window(BSW)is constructed to cover the position of the optimal hypothesis block as much as possible.To maximize the availability of reference frames,Nearby reference frame information(NRFI)is designed to reconstruct the current block.The proposed method effectively suppresses the influence of the fluctuation of the prediction block on reconstruction and improves the reconstruction performance.Experimental results showthat the proposed compressed sensing-based high-quality adaptive video reconstruction optimization method significantly improves the reconstruction performance in both objective and supervisor quality.

关 键 词：Compressed sensing OPBS block-level search window nearby reference frame information evolutionary algorithm 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]