báo cáo hóa học:" Denoising Algorithm for the 3D Depth Map Sequences Based on Multihypothesis Motion Estimation"

Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí sinh học đề tài : Denoising Algorithm for the 3D Depth Map Sequences Based on Multihypothesis Motion Estimation | EURASIP Journal on Advances in Signal Processing SpringerOpen0 This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text HTML versions will be made available soon. Denoising Algorithm for the 3D Depth Map Sequences Based on Multihypothesis Motion Estimation EURASIP Journal on Advances in Signal Processing 2011 2011 131 doi 1687-6180-2011-131 Ljubomir Jovanov ljj@ Aleksandra Pizurica sanja@ Wilfried Philips philips@ ISSN 1687-6180 Article type Research Submission date 5 June 2011 Acceptance date 12 December 2011 Publication date 12 December 2011 Article URL http content 2011 1 131 This peer-reviewed article was published immediately upon acceptance. It can be downloaded printed and distributed freely for any purposes see copyright notice below . For information about publishing your research in EURASIP Journal on Advances in Signal Processing go to http authors instructions For information about other SpringerOpen publications go to http 2011 Jovanov etal. licensee Springer. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Noname manuscript No. will be inserted by the editor Denoising of 3D time-of-flight video using multihypothesis motion estimation Ljubomir Jovanov Aleksandra Pizurica and Wilfried Philips Ghent University-TELIN-IPI-IBBT Sint-Pietersnieuwstraat 41 B-9000 Gent Belgium Corresponding author ljj@ Email addresses AP sanja@ WP philips@ Abstract This article proposes an efficient wavelet-based depth video denoising approach based on a multihypothesis motion estimation aimed specifically at time-of-flight depth cameras. We first .

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