Journal of Information Hiding and Multimedia Signal Processing ©2014 ISSN 2073-4212
Ubiquitous International
Xue Zhang1;3, Anhong Wang1, Bing Zeng2, and Lei Liu3
Received May, 2013; revised September, 2013
Abstract. Compressed sensing is a state-of-the-art technology which can signicantly
reduce the number of sampled data in sparse signal acquisition. This paper studies the dis-
tributed compressed sensing (DISCOS) of video signals. To this end, we propose adaptive
adjustments to the block-based (local) measurement rate, the frame-based (global) mea-
surement rate, and the sparse dictionary size, thus forming an adaptive DISCOS scheme
(aDISCOS). Two adjustments on measurement rates are based on the spatial and tem-
poral sparsity that is obtained through an analysis on the block-type and the inter-frame
motion, while the sparse dictionary size is adjusted according to the motion information.
All analyses are implemented at the decoder side and the analysis results are sent back
to the encoder via a feedback channel, yielding a low-complexity encoding (to meet the
equirement of a distributed coding scheme). Simulation results show that the proposed
aDISCOS achieves a superior rate-distortion performance as well as better visual quality,
when compared with the original DISCOS scheme.
Keywords: Compressed sensing, distributed compressed sensing, adaptive sampling,
sparse dictionary
دانلود مقاله Adaptive Distributed Compressed Video Sensing