Rate-Distortion Optimized Distributed Compressive Video Sensing
Summary :
Distributed compressive video sensing (DCVS) is an emerging low-complexity video coding framework which integrates the merits of distributed video coding (DVC) and compressive sensing (CS). In this paper, we propose a novel rate-distortion optimized DCVS codec, which takes advantage of a rate-distortion optimization (RDO) model based on the estimated correlation noise (CN) between a non-key frame and its side information (SI) to determine the optimal measurements allocation for the non-key frame. Because the actual CN can be more accurately recovered by our DCVS codec, it leads to more faithful reconstruction of the non-key frames by adding the recovered CN to the SI. The experimental results reveal that our DCVS codec significantly outperforms the legacy DCVS codecs in terms of both objective and subjective performance.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E99-A No.6 pp.1272-1276
- Publication Date
- 2016/06/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E99.A.1272
- Type of Manuscript
- LETTER
- Category
- Multimedia Environment Technology
Authors
Jin XU
UESTC
Yuansong QIAO
Athlone Institute of Technology
Quan WEN
UESTC
Keyword
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Jin XU, Yuansong QIAO, Quan WEN, "Rate-Distortion Optimized Distributed Compressive Video Sensing" in IEICE TRANSACTIONS on Fundamentals,
vol. E99-A, no. 6, pp. 1272-1276, June 2016, doi: 10.1587/transfun.E99.A.1272.
Abstract: Distributed compressive video sensing (DCVS) is an emerging low-complexity video coding framework which integrates the merits of distributed video coding (DVC) and compressive sensing (CS). In this paper, we propose a novel rate-distortion optimized DCVS codec, which takes advantage of a rate-distortion optimization (RDO) model based on the estimated correlation noise (CN) between a non-key frame and its side information (SI) to determine the optimal measurements allocation for the non-key frame. Because the actual CN can be more accurately recovered by our DCVS codec, it leads to more faithful reconstruction of the non-key frames by adding the recovered CN to the SI. The experimental results reveal that our DCVS codec significantly outperforms the legacy DCVS codecs in terms of both objective and subjective performance.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E99.A.1272/_p
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@ARTICLE{e99-a_6_1272,
author={Jin XU, Yuansong QIAO, Quan WEN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Rate-Distortion Optimized Distributed Compressive Video Sensing},
year={2016},
volume={E99-A},
number={6},
pages={1272-1276},
abstract={Distributed compressive video sensing (DCVS) is an emerging low-complexity video coding framework which integrates the merits of distributed video coding (DVC) and compressive sensing (CS). In this paper, we propose a novel rate-distortion optimized DCVS codec, which takes advantage of a rate-distortion optimization (RDO) model based on the estimated correlation noise (CN) between a non-key frame and its side information (SI) to determine the optimal measurements allocation for the non-key frame. Because the actual CN can be more accurately recovered by our DCVS codec, it leads to more faithful reconstruction of the non-key frames by adding the recovered CN to the SI. The experimental results reveal that our DCVS codec significantly outperforms the legacy DCVS codecs in terms of both objective and subjective performance.},
keywords={},
doi={10.1587/transfun.E99.A.1272},
ISSN={1745-1337},
month={June},}
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TY - JOUR
TI - Rate-Distortion Optimized Distributed Compressive Video Sensing
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1272
EP - 1276
AU - Jin XU
AU - Yuansong QIAO
AU - Quan WEN
PY - 2016
DO - 10.1587/transfun.E99.A.1272
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E99-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2016
AB - Distributed compressive video sensing (DCVS) is an emerging low-complexity video coding framework which integrates the merits of distributed video coding (DVC) and compressive sensing (CS). In this paper, we propose a novel rate-distortion optimized DCVS codec, which takes advantage of a rate-distortion optimization (RDO) model based on the estimated correlation noise (CN) between a non-key frame and its side information (SI) to determine the optimal measurements allocation for the non-key frame. Because the actual CN can be more accurately recovered by our DCVS codec, it leads to more faithful reconstruction of the non-key frames by adding the recovered CN to the SI. The experimental results reveal that our DCVS codec significantly outperforms the legacy DCVS codecs in terms of both objective and subjective performance.
ER -
English
