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Hierarchical Stereo Matching in Two-Scale Space for Cyber-Physical System

Dense disparity map estimation from a high-resolution stereo image is a very difficult problem in terms of both matching accuracy and computation efficiency. Thus, an exhaustive disparity search at full resolution is required. In general, examining more pixels in the stereo view results in more ambi...

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Autores principales: Choi, Eunah, Lee, Sangyoon, Hong, Hyunki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539473/
https://www.ncbi.nlm.nih.gov/pubmed/28753991
http://dx.doi.org/10.3390/s17071680
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author Choi, Eunah
Lee, Sangyoon
Hong, Hyunki
author_facet Choi, Eunah
Lee, Sangyoon
Hong, Hyunki
author_sort Choi, Eunah
collection PubMed
description Dense disparity map estimation from a high-resolution stereo image is a very difficult problem in terms of both matching accuracy and computation efficiency. Thus, an exhaustive disparity search at full resolution is required. In general, examining more pixels in the stereo view results in more ambiguous correspondences. When a high-resolution image is down-sampled, the high-frequency components of the fine-scaled image are at risk of disappearing in the coarse-resolution image. Furthermore, if erroneous disparity estimates caused by missing high-frequency components are propagated across scale space, ultimately, false disparity estimates are obtained. To solve these problems, we introduce an efficient hierarchical stereo matching method in two-scale space. This method applies disparity estimation to the reduced-resolution image, and the disparity result is then up-sampled to the original resolution. The disparity estimation values of the high-frequency (or edge component) regions of the full-resolution image are combined with the up-sampled disparity results. In this study, we extracted the high-frequency areas from the scale-space representation by using difference of Gaussian (DoG) or found edge components, using a Canny operator. Then, edge-aware disparity propagation was used to refine the disparity map. The experimental results show that the proposed algorithm outperforms previous methods.
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spelling pubmed-55394732017-08-11 Hierarchical Stereo Matching in Two-Scale Space for Cyber-Physical System Choi, Eunah Lee, Sangyoon Hong, Hyunki Sensors (Basel) Article Dense disparity map estimation from a high-resolution stereo image is a very difficult problem in terms of both matching accuracy and computation efficiency. Thus, an exhaustive disparity search at full resolution is required. In general, examining more pixels in the stereo view results in more ambiguous correspondences. When a high-resolution image is down-sampled, the high-frequency components of the fine-scaled image are at risk of disappearing in the coarse-resolution image. Furthermore, if erroneous disparity estimates caused by missing high-frequency components are propagated across scale space, ultimately, false disparity estimates are obtained. To solve these problems, we introduce an efficient hierarchical stereo matching method in two-scale space. This method applies disparity estimation to the reduced-resolution image, and the disparity result is then up-sampled to the original resolution. The disparity estimation values of the high-frequency (or edge component) regions of the full-resolution image are combined with the up-sampled disparity results. In this study, we extracted the high-frequency areas from the scale-space representation by using difference of Gaussian (DoG) or found edge components, using a Canny operator. Then, edge-aware disparity propagation was used to refine the disparity map. The experimental results show that the proposed algorithm outperforms previous methods. MDPI 2017-07-21 /pmc/articles/PMC5539473/ /pubmed/28753991 http://dx.doi.org/10.3390/s17071680 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Choi, Eunah
Lee, Sangyoon
Hong, Hyunki
Hierarchical Stereo Matching in Two-Scale Space for Cyber-Physical System
title Hierarchical Stereo Matching in Two-Scale Space for Cyber-Physical System
title_full Hierarchical Stereo Matching in Two-Scale Space for Cyber-Physical System
title_fullStr Hierarchical Stereo Matching in Two-Scale Space for Cyber-Physical System
title_full_unstemmed Hierarchical Stereo Matching in Two-Scale Space for Cyber-Physical System
title_short Hierarchical Stereo Matching in Two-Scale Space for Cyber-Physical System
title_sort hierarchical stereo matching in two-scale space for cyber-physical system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539473/
https://www.ncbi.nlm.nih.gov/pubmed/28753991
http://dx.doi.org/10.3390/s17071680
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