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In transform-domain distributed video coding (DVC), the correlation noises (denoted as N) between the source block and its temporal predictor can be modeled as Laplacian random variables. In this paper we propose that the noises (denoted as N′) between the source block and its co-located block in a reference frame can also be modeled as Laplacian random variables. Furthermore, it is possible to exploit the relationship between N and N′ to improve the performance of the DVC system. A practical scheme based on theoretical insights, the hash signature saving scheme, is proposed. Experimental results show that the proposed scheme saves on average 83.2% of hash signatures, 13.3% of bit-rate, and 3.9% of encoding time.
In this paper we propose that the noises (denoted as N ’) between the source block and its temporal predictor can be modeled as Laplacian random variables. the source block and its co-located block in a reference frame can also be modeled as Laplacian random variables. Furthermore, it is possible to exploit the relationship between N and N ’to improve the performance of the DVC system. A practical scheme based on theoretical results, the hash signature saving scheme, is proposed. Experimental results show that the proposed scheme saves on average 83.2% of hash signatures, 13.3% of bit-rate, and 3.9% of encoding time.