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Rate-Distortion Optimized Distributed Compressive Video Sensing
Jin XU Yuansong QIAO Quan WEN
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2016/06/01
Online ISSN: 1745-1337
Type of Manuscript: LETTER
Category: Multimedia Environment Technology
distributed compressive video sensing, rate-distortion optimized measurements allocation, adaptive sparse recovery with SI,
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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.