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Stereo Matching by Filtering-Based Disparity Propagation

Stereo matching is essential and fundamental in computer vision tasks. In this paper, a novel stereo matching algorithm based on disparity propagation using edge-aware filtering is proposed. By extracting disparity subsets for reliable points and customizing the cost volume, the initial disparity ma...

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Detalles Bibliográficos
Autores principales: Wang, Xingzheng, Tian, Yushi, Wang, Haoqian, Zhang, Yongbing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5023157/
https://www.ncbi.nlm.nih.gov/pubmed/27626800
http://dx.doi.org/10.1371/journal.pone.0162939
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author Wang, Xingzheng
Tian, Yushi
Wang, Haoqian
Zhang, Yongbing
author_facet Wang, Xingzheng
Tian, Yushi
Wang, Haoqian
Zhang, Yongbing
author_sort Wang, Xingzheng
collection PubMed
description Stereo matching is essential and fundamental in computer vision tasks. In this paper, a novel stereo matching algorithm based on disparity propagation using edge-aware filtering is proposed. By extracting disparity subsets for reliable points and customizing the cost volume, the initial disparity map is refined through filtering-based disparity propagation. Then, an edge-aware filter with low computational complexity is adopted to formulate the cost column, which makes the proposed method independent on the local window size. Experimental results demonstrate the effectiveness of the proposed scheme. Bad pixels in our output disparity map are considerably decreased. The proposed method greatly outperforms the adaptive support-weight approach and other conditional window-based local stereo matching algorithms.
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spelling pubmed-50231572016-09-27 Stereo Matching by Filtering-Based Disparity Propagation Wang, Xingzheng Tian, Yushi Wang, Haoqian Zhang, Yongbing PLoS One Research Article Stereo matching is essential and fundamental in computer vision tasks. In this paper, a novel stereo matching algorithm based on disparity propagation using edge-aware filtering is proposed. By extracting disparity subsets for reliable points and customizing the cost volume, the initial disparity map is refined through filtering-based disparity propagation. Then, an edge-aware filter with low computational complexity is adopted to formulate the cost column, which makes the proposed method independent on the local window size. Experimental results demonstrate the effectiveness of the proposed scheme. Bad pixels in our output disparity map are considerably decreased. The proposed method greatly outperforms the adaptive support-weight approach and other conditional window-based local stereo matching algorithms. Public Library of Science 2016-09-14 /pmc/articles/PMC5023157/ /pubmed/27626800 http://dx.doi.org/10.1371/journal.pone.0162939 Text en © 2016 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wang, Xingzheng
Tian, Yushi
Wang, Haoqian
Zhang, Yongbing
Stereo Matching by Filtering-Based Disparity Propagation
title Stereo Matching by Filtering-Based Disparity Propagation
title_full Stereo Matching by Filtering-Based Disparity Propagation
title_fullStr Stereo Matching by Filtering-Based Disparity Propagation
title_full_unstemmed Stereo Matching by Filtering-Based Disparity Propagation
title_short Stereo Matching by Filtering-Based Disparity Propagation
title_sort stereo matching by filtering-based disparity propagation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5023157/
https://www.ncbi.nlm.nih.gov/pubmed/27626800
http://dx.doi.org/10.1371/journal.pone.0162939
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AT zhangyongbing stereomatchingbyfilteringbaseddisparitypropagation