Electronics, Communication & Automation Technology

Residual Structure Characteristics- Based Block Classifying Reconstruction Algorithm for CVS

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  • School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
杨春玲( 1970-) ,女,博士,教授,主要从事图像/视频压缩感知研究.

Received date: 2016-05-25

  Revised date: 2016-11-24

  Online published: 2017-02-02

Supported by

Supported by the Natural Science Foundation of Guangdong Province of China( 2016A030313455)

Abstract

Most existing compressed video sensing ( CVS) algorithms with best reconstruction performance adopt a “prediction-residual reconstruction”strategy,which helps obtain high reconstruction quality by taking good advantage of intra-frame and inter-frame correlation.However,all of them ignore the residual structure characteristics and simply use SPL reconstruction algorithm which is only suitable for natural image compressed sensing.In order to solve this problem,a block classifying reconstruction algorithm on the basis of residual structure characteristics is proposed,which firstly classifies residual blocks according to their average energy and then adopts suitable algorithms to reconstruct residual blocks corresponding to their structure characteristics.Simulated results show that the proposed algorithm helps achieve higher reconstruction quality than SPL algorithm for video sequences with fast movements.

Cite this article

YANG Chun-ling LI Wen-hao . Residual Structure Characteristics- Based Block Classifying Reconstruction Algorithm for CVS[J]. Journal of South China University of Technology(Natural Science), 2017 , 45(3) : 1 -10 . DOI: 10.3969/j.issn.1000-565X.2017.03.001

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