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Layer based multi-view image compression

dc.contributor.authorGelman, Andriyen_GB
dc.contributor.authorDragotti, Pier Luigien_GB
dc.contributor.authorVelisavljević, Vladanen_GB
dc.date.accessioned2013-05-22T11:18:46Z
dc.date.available2013-05-22T11:18:46Z
dc.date.issued2009
dc.identifier.citationGelman, A., Dragotti, P.L. and Velisavljevic, V. (2009) 'Layer-based multiview image compression', Proceedings of the 5th International ICST Mobile Multimedia Communications Conference (MobiMedia), London, UK, 7-9 September. London: ICST, article 18.en_GB
dc.identifier.isbn9789639799622
dc.identifier.doi10.4108/ICST.MOBIMEDIA2009.7489
dc.identifier.urihttp://hdl.handle.net/10547/292572
dc.description.abstractThe authors propose a compression algorithm for an array of multiview images. First, we apply a segmentation algorithm to partition the data into coherent layers and significantly reduce the number of images required for artifact-free rendering. Then, we exploit the coherence in each layer by applying a 1D disparity compensated wavelet transform across the views followed by a 2D SA-DWT on each of the spatial subbands. Finally, the data is entropy coded using a modified version of EBCOT. Experimental results show that our coder outperforms state-of-the-art H.264/AVC at low bit-rates and intra-image JPEG-2000 over the complete range of bit-rates. Furthermore, unlike other multi-view image compression techniques, our implementation does not rely on estimating a 3D geometric model of the scene.
dc.language.isoenen
dc.publisherICSTen_GB
dc.relation.urlhttp://eudl.eu/doi/10.4108/ICST.MOBIMEDIA2009.7489en_GB
dc.relation.urlhttp://dl.acm.org/citation.cfm?id=1653564en_GB
dc.subjectmulti-view imageen_GB
dc.subjectfree-viewpoint renderingen_GB
dc.subjectcompressionen_GB
dc.subject3D waveleten_GB
dc.titleLayer based multi-view image compressionen
dc.typeConference papers, meetings and proceedingsen
html.description.abstractThe authors propose a compression algorithm for an array of multiview images. First, we apply a segmentation algorithm to partition the data into coherent layers and significantly reduce the number of images required for artifact-free rendering. Then, we exploit the coherence in each layer by applying a 1D disparity compensated wavelet transform across the views followed by a 2D SA-DWT on each of the spatial subbands. Finally, the data is entropy coded using a modified version of EBCOT. Experimental results show that our coder outperforms state-of-the-art H.264/AVC at low bit-rates and intra-image JPEG-2000 over the complete range of bit-rates. Furthermore, unlike other multi-view image compression techniques, our implementation does not rely on estimating a 3D geometric model of the scene.


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