Title :
An unequally protected Distributed Compressed Video Sensing algorithm
Author :
Li, Bin ; Zhu, Xuqi ; Liu, Yu ; Zhang, Lin
Author_Institution :
Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
Distributed Compressed Video Sensing (DCVS) has developed as one of the efficient solutions that guarantee low complexity video compression. In this paper, a novel DCVS algorithm with unequal protection of the video signal´s elements is proposed. The new algorithm utilizes not only the sparsity and probability distribution of the video signal but also its particular unequal significance feature. Based on this feature, we design the structured irregular low-density sensing matrix to sample the signal. From the analysis and simulation results, it is confirmed that our method has higher recovery quality than the conventional Bayesian Compressed Sensing (CS) using Belief Propagation (BP). Moreover, the excellent noise-resilience of BP is preserved in our algorithm comparing to the DCVS schemes using optimization recovery.
Keywords :
compressed sensing; data compression; statistical distributions; video coding; Bayesian compressed sensing; DCVS algorithm; belief propagation; distributed compressed video sensing algorithm; low complexity video compression; optimization recovery; probability distribution; structured irregular low-density sensing matrix; video signal sparsity; Algorithm design and analysis; Decoding; Discrete cosine transforms; PSNR; Parity check codes; Pollution measurement; Sensors; Bayesian compressed sensing; belief propagation; distributed video coding; unequal protection;
Conference_Titel :
Visual Communications and Image Processing (VCIP), 2011 IEEE
Conference_Location :
Tainan
Print_ISBN :
978-1-4577-1321-7
Electronic_ISBN :
978-1-4577-1320-0
DOI :
10.1109/VCIP.2011.6115935
