Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/273
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dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorChan, YL-
dc.creatorSiu, WC-
dc.date.accessioned2014-12-11T08:23:12Z-
dc.date.available2014-12-11T08:23:12Z-
dc.identifier.isbn0-7803-7663-3-
dc.identifier.urihttp://hdl.handle.net/10397/273-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rights© 2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_US
dc.rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.en_US
dc.subjectBlock motion estimationen_US
dc.subjectHilbert-grouped partial distortion search algorithmen_US
dc.subjectPartial distortion searchen_US
dc.subjectSum of absolute differenceen_US
dc.titleAn adaptive partial distortion search for block motion estimationen_US
dc.typeConference Paperen_US
dcterms.abstractFast search algorithms for block motion estimation reduce the set of possible displacements for locating the motion vector. All algorithms produce some quality degradation of the predicted image. To reduce the computational complexity of the full search algorithm without introducing any loss in the predicted image, we propose a Hilbert-grouped partial distortion search algorithm (HGPDS) by grouping the representative pixels based on pixel activities in the hilbert scan. By using the grouped information and computing the accumulated partial distortion of the representative pixels before that of other pixels, impossible candidates can be rejected sooner and the remaining computation involved in the matching criterion can be reduced remarkably. In addition, we also suggest a smart search strategy which is an excellent complement of the HGPDS to form an efficient partial distortion search algorithm. The new search strategy rearranges the search order such that the most possible candidates are searched first and this rearrangement will increase the probability of early rejection of impossible motion vectors. Simulation results show that the proposed algorithm has a significant computational speed-up and is the fastest when compared to the conventional partial distortion search algorithms.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitation2003 IEEE International Conference on Acoustics, Speech, and Signal Processing : proceedings : April 6-10, 2003, Hong Kong Exhibition and Convention Centre, Hong Kong, p. III153-III156-
dcterms.issued2003-
dc.identifier.isiWOS:000185390600039-
dc.identifier.scopus2-s2.0-0141676441-
dc.identifier.rosgroupidr11605-
dc.description.ros2002-2003 > Academic research: refereed > Refereed conference paper-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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