Perceptually-aware distributed compressive video sensing

Jin Xu, Soufiene Djahel, Yuansong Qiao, Zhizhong Fu

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Citation (Scopus)

    Abstract

    By combining the advantages of distributed video coding (DVC) and compressive sensing (CS), distributed compressive video sensing (DCVS) poses itself as a very promising low-complexity video coding framework for distributed applications. In order to improve the rate-distortion performance of DCVS, much research efforts have been focused on exploring the best ways to utilize the spatial/temporal redundancy of video data to achieve efficient sparse representation and reconstruction at the decoder. Unlike the existing DCVS schemes, we aim to improve the perceptual rate-distortion performance of DCVS by designing a novel perceptually-aware DCVS codec. Based on online estimation of the correlation noise between a non-key frame and its side information (SI) considering the effect of human visual system (HVS), we design an efficient perceptually-aware block compressive sensing scheme for a non-key frame in our DCVS codec, in order to more accurately reconstruct the salient regions in the video frames. The obtained experimental results reveal that our DCVS codec outperforms the legacy DCVS codecs in terms of the perceptual rate-distortion performance.

    Original languageEnglish
    Title of host publication2015 Visual Communications and Image Processing, VCIP 2015
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781467373142
    DOIs
    Publication statusPublished - 2015
    EventVisual Communications and Image Processing, VCIP 2015 - Singapore, Singapore
    Duration: 13 Dec 201516 Dec 2015

    Publication series

    Name2015 Visual Communications and Image Processing, VCIP 2015

    Conference

    ConferenceVisual Communications and Image Processing, VCIP 2015
    Country/TerritorySingapore
    CitySingapore
    Period13/12/1516/12/15

    Keywords

    • Compressive Sensing
    • Distributed Video Coding
    • Human Visual System
    • Perceptual Coding

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