Computer Science

Computer Science ›› 2019, Vol. 46 ›› Issue (1): 291-296.doi: 10.11896／j.issn.1002-137X.2019.01.045

• Graphics ,Image & Pattern Recognition • Previous Articles     Next Articles

Multi-hypothesis Reconstruction Algorithm of DCVS Based on Weighted Non-local Similarity

DU Xiu-li, HU Xing, CHEN Bo, QIU Shao-ming   

  1. (Key Laboratory of Communication and Network,Dalian University,Dalian,Liaoning 116622,China)
    (College of Information Engineering,Dalian University,Dalian,Liaoning 116622,China)
  • Received:2017-10-14 Online:2019-01-15 Published:2019-02-25

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Abstract: Multi-hypothesis reconstruction algorithm of DCVS (Distributed Compressed Video Sensing) introduces the idea of multi-hypothesis prediction motion estimation of traditional video encoding into the DCVS encoding system,thus improving the reconstruction quality for video sequence.In this algorithm,the blocks with big changes adopt the information of current frame neighborhood blocks as a reference,and its performance needs to be improved when the neighborhood of frame contains lots of textures and details.Through improving the idea of non-local similarity,this paper proposed a multi-hypothesis reconstruction algorithm of DCVS based on weighted non-local similarity.In the improved algorithm,the weighted non-local similarity is adopted to search the self-similar blocks in adjacent reconstructed frames for the texture block in the block with big changes,finally generating supplementary reconstruction information blocks.For text non-texture blocks,the weighted non-local similarity is utilized to generate similar blocks.For the blocks with small changes,inter-frame multi-hypothesis reconstruction is adopted,and non-critical frame reconstruction is assisted.Simulation results based on different video sequences show that the proposed algorithm can improve the reconstruction quality of video sequence effectively,and has better reconstructed SSIM and PSNR,and the PSNR is about 1dB higher.

Key words: Compressed sensing, Distributed video coding, Multiple hypothesis reconstruction, Non-local similarity

CLC Number: 

  • TN919.8
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