Distributed Compressive Video Sensing with Adaptive Measurements Based on Structural Similarity

This paper presents a Distributed compressive video sensing scheme with Adaptive measurements （DCVS-AM）. In this approach, the key frame in each Group of pictures （GOP） is coded by Compressive sensing （CS） with a fixed measurement rate; whereas other frames in the same GOP are compressed by an adapt...

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Bibliographic Details
Published in:电子学报：英文版 2013-07, Vol.22 (3), p.594-598
Main Author: LIU Zhuo WANG Anhong ZENG Bing ZHANG Xue BAI Huihui LI Zhihong
Format: Article
Language:English
Subjects:
关键帧
分布式
相似度
结构
编码压缩
自适应压缩
自适应测量
视频检测
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Summary:This paper presents a Distributed compressive video sensing scheme with Adaptive measurements （DCVS-AM）. In this approach, the key frame in each Group of pictures （GOP） is coded by Compressive sensing （CS） with a fixed measurement rate; whereas other frames in the same GOP are compressed by an adaptive random projection in two stages, yielding the Adaptive compressive sensing （ACS） frames. The first stage uses a small and fixed measurement rate and recovers a coarse version. In the second stage, each coarse-version ACS-frame together with its proceeding and following key frames will go through a joint analysis at the decoder side and the analysis result - Structural similarity （SSIM） that is based on a motion-guided interpolation and calculated in a multilevel discrete wavelet transform domain - is sent back to the encoder side to facilitate a re-sampling of the ACS-frame with an adaptive measurement rate. Experimental results show that our proposed DCVS-AM consistently outperforms the state-of-the-art DCVS with a fixed measurement.
ISSN:1022-4653