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Scalable video coding technologies provide adaptive video applications in heterogeneous and polytropical conditions. However, the highly hierarchical feature makes the loss or unsuccessful recovery of the base-layer to be catastrophic. In this paper, a distributed scalable video coding scheme using the new advances of compressed sensing is proposed to solve this problem at the energy-constrained encoder...
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...
Distributed compressive video sensing (DCVS), aiming at capturing and compressing video data simultaneously, is an emerging field which exploits both intra- and inter-frame correlation. In this paper, we present a new algorithm based on smoothed ℓ0 norm (SL0) which tries to directly minimize the ℓ0 norm to decode a Wyner-Ziv frame when parts of its correlated key frame's support is known as side information...
Event Detection is one of the main applications of wireless sensor networks (WSN). However, due to the noisy sensed data of sensors and the wireless channel noise, it's difficult to guarantee the accuracy of detection, especially in multiple event detection. In this paper, we proposed a multiple event detection scheme using compressed sensing (CS). By analogy with CS problem, the efficient recovery...
Compressed Sensing (CS) has developed rapidly as an innovation in signal processing domain. Considering the situation that there are multiple sparse signals with redundancy, the correlation between them need to be properly utilized for further compression. To this end, a CS scheme based on Belief Propagation (BP) algorithm is proposed to compress correlated sparse (compressible) signals in this paper...
Distributed compressive sensing (DCS) is a new technique that provides a low-complexity sub-Nyquist signal acquisition and reconstruction via a small number of random linear projections. In this paper, we propose sparse filter correlation model (SFCM) to exploit the correlations among successive video frames under the framework of distributed compressive video sensing (DCVS). At the central decoder,...
Distributed compression of correlated sources has been discussed much in wireless sensor networks, while the error-resilient implementation of this efficient coding strategy is one of the crucial issues for applications. In this paper, a symmetric Distributed Joint Source-Channel Coding (DJSCC) scheme is proposed by using Raptor codes for the independent channels case. The channel noise and the correlation...
Multiple nodes sensing the common target is the most popular application of the Wireless Sensor Networks (WSNs). Pure distributed compression of multiple correlated sources has been discussed much in the related literature, while taking the noisy communication channels into account is more suitable for the actual scenario. In this paper, a practical Distributed Joint Source-Channel Coding (DJSCC)...
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