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Netw."],"published-print":{"date-parts":[[2014,1]]},"abstract":"<jats:p>Wyner-Ziv video coding 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 video coding 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 video coding (e.g., up to 42.03% over DISCOVER) as well as versus alternative state-of-the-art schemes refining the side-information.<\/jats:p>","DOI":"10.1145\/2530279","type":"journal-article","created":{"date-parts":[[2014,1,28]],"date-time":"2014-01-28T13:49:22Z","timestamp":1390916962000},"page":"1-34","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Progressively refined wyner-ziv video coding for visual sensors"],"prefix":"10.1145","volume":"10","author":[{"given":"Nikos","family":"Deligiannis","sequence":"first","affiliation":[{"name":"Vrije Universiteit Brussel, Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frederik","family":"Verbist","sequence":"additional","affiliation":[{"name":"Vrije Universiteit Brussel, Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J\u00fcrgen","family":"Slowack","sequence":"additional","affiliation":[{"name":"Ghent University, Ghent, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rik van de","family":"Walle","sequence":"additional","affiliation":[{"name":"Ghent University, Ghent, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Schelkens","sequence":"additional","affiliation":[{"name":"Vrije Universiteit Brussel, Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adrian","family":"Munteanu","sequence":"additional","affiliation":[{"name":"Vrije Universiteit Brussel, Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2014,1,31]]},"reference":[{"volume-title":"Proceedings of the IEEE International Conference on Image Processing (ICIP'04)","author":"Aaron A.","key":"e_1_2_1_1_1"},{"volume-title":"Proceedings of the 19th European Signal Processing Conference (EUSIPCO'11)","author":"Abou-Elailah A.","key":"e_1_2_1_2_1"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1049\/el:20060302"},{"volume-title":"Proceedings of the Annual Conference on Information Sciences and Systems (CISS'09)","author":"Ahmad J. 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