Distributed Compressive Video Sensing with Adaptive Measurements Based on Structural Similarity  

作　　者：LIU Zhuo WANG Anhong ZENG Bing ZHANG Xue BAI Huihui LI Zhihong 

机构地区：[1]Institute of Digital Media and Communication, Taiyuan University of Science and Technology, Taiyuan 030024, China [2]Hong Kong University of Science and Technology, Hong Kong SAR, China [3]Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China

出　　处：《Chinese Journal of Electronics》2013年第3期594-598,共5页电子学报（英文版）

基　　金：This work is supported in part by Sino-Singapore Joint Research Projet （No.2010DFA11010）, the National Natural Science Foundation of China （No.61073142, No.61272262, No.61210006, No.61272051）, the Doctor Startup Foundation of TYUST （No.20092011）, the International Cooperative Program of Shanxi Province （No.2011081055）, the Shanxi Provincial Foundation for Leaders of Disciplines in Science （No.20111022）, Shanxi Province Talent Introduction and Development Fund （2011）, Shanxi Provincial Natural Science Foundation （No.2012011014-3）, the College Students Innovative Program of Taiyuan （No. 120164077）.

摘　　要：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.

关 键 词：Distributed compressive video sensing （DCVS） Adaptive measurement rate Structural similarity （SSIM） Discrete wavelet transform （DWT）. 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TN911.22[自动化与计算机技术—计算机科学与技术]