Recent advances in wireless visual sensor technology, have been calling for innovative architectures realizing efficient videocoding under stringent processing and energy restrictions. driven by profound findings in ...
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ISBN:
(纸本)9781457717079
Recent advances in wireless visual sensor technology, have been calling for innovative architectures realizing efficient videocoding under stringent processing and energy restrictions. driven by profound findings in network information theory, Wyner-Ziv videocoding constitutes a suitable paradigm for video sensor networks. This work presents a novel hash-driven Wyner-Ziv videocoding architecture for visual sensors, which coarsely encodes a low resolution version of each Wyner-Ziv frame to facilitate accurate motion-compensated prediction at the decoder. The proposed method for side-information generation comprises hash-based multi-hypothesis pixel-based prediction. Once critical Wyner-Ziv information is decoded, the derived dense motion field is further enhanced. Experimental validation illustrates that the proposed hash-driven codec achieves significant compression gains with respect to state-of-the-art Wyner-Ziv videocoding, even under demanding conditions.
Wyner-Ziv videocoding constitutes an alluring paradigm for visual sensor networks, offering efficient video compression with low complexity encoding characteristics. This work presents a novel hash-driven Wyner-Ziv v...
详细信息
Wyner-Ziv videocoding constitutes an alluring paradigm for visual sensor networks, offering efficient video compression with low complexity encoding characteristics. This work presents a novel hash-driven Wyner-Ziv videocoding architecture for visual sensors, implementing the principles of successively refined Wyner-Ziv coding. To this end, so-called side-information refinement levels are constructed for a number of grouped frequency bands of the discrete cosine transform. The proposed codec creates side-information by means of an original overlapped block motion estimation and pixel-based multihypothesis prediction technique, specifically built around the pursued refinement strategy. The quality of the side-information generated at every refinement level is successively improved, leading to gradually enhanced Wyner-Ziv coding performance. Additionally, this work explores several temporal prediction structures, including a new hierarchical unidirectional prediction structure, providing both temporal scalability and low delay coding. Experimental results include a thorough evaluation of our novel Wyner-Ziv codec, assessing the impact of the proposed successive refinement scheme and the supported temporal prediction structures for a wide range of hash configurations and group of pictures sizes. The results report significant compression gains with respect to benchmark systems in Wyner-Ziv videocoding (e. g., up to 42.03% over DISCOVER) as well as versus alternative state-of-the-art schemes refining the side-information.
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