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)


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.
Number of pages4
ISBN (Electronic)9781467373142, 9781467373135
Publication statusPublished - 25 Apr 2016
Externally publishedYes
EventVisual Communications and Image Processing 2015 - Singapore, Singapore
Duration: 13 Dec 201516 Dec 2015


ConferenceVisual Communications and Image Processing 2015
Abbreviated titleVCIP 2015


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