Perceptually-aware Distributed Compressive Video Sensing

Jin Xu; Soufiene Djahel; Yuansong Qiao; Zhizhong Fu

doi:10.1109/VCIP.2015.7457802

Perceptually-aware Distributed Compressive Video Sensing

Jin Xu, Soufiene Djahel, Yuansong Qiao, Zhizhong Fu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	2015 Visual Communications and Image Processing, VCIP 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	4
ISBN (Electronic)	9781467373142, 9781467373135
DOIs	https://doi.org/10.1109/VCIP.2015.7457802
Publication status	Published - 25 Apr 2016
Externally published	Yes
Event	Visual Communications and Image Processing 2015 - Singapore, Singapore Duration: 13 Dec 2015 → 16 Dec 2015

Conference

Conference	Visual Communications and Image Processing 2015
Abbreviated title	VCIP 2015
Country/Territory	Singapore
City	Singapore
Period	13/12/15 → 16/12/15

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title = "Perceptually-aware Distributed Compressive Video Sensing",

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.",

keywords = "Compressive Sensing, Distributed Video Coding, Human Visual System, Perceptual Coding",

author = "Jin Xu and Soufiene Djahel and Yuansong Qiao and Zhizhong Fu",

note = "Funding Information: This work was supported in part by the scholarship from China Scholarship Council (No.201308515002) and Science Foundation Ireland grant (10/CE/I1855, 13/RC/2094) Publisher Copyright: {\textcopyright} 2015 IEEE.; Visual Communications and Image Processing 2015, VCIP 2015 ; Conference date: 13-12-2015 Through 16-12-2015",

year = "2016",

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doi = "10.1109/VCIP.2015.7457802",

language = "English",

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AU - Xu, Jin

AU - Djahel, Soufiene

AU - Qiao, Yuansong

AU - Fu, Zhizhong

N1 - Funding Information: This work was supported in part by the scholarship from China Scholarship Council (No.201308515002) and Science Foundation Ireland grant (10/CE/I1855, 13/RC/2094) Publisher Copyright: © 2015 IEEE.

PY - 2016/4/25

Y1 - 2016/4/25

N2 - 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.

AB - 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.

KW - Compressive Sensing

KW - Distributed Video Coding

KW - Human Visual System

KW - Perceptual Coding

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U2 - 10.1109/VCIP.2015.7457802

DO - 10.1109/VCIP.2015.7457802

M3 - Conference contribution

AN - SCOPUS:84979043491

BT - 2015 Visual Communications and Image Processing, VCIP 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - Visual Communications and Image Processing 2015

Y2 - 13 December 2015 through 16 December 2015

ER -

Perceptually-aware Distributed Compressive Video Sensing

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