A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas

Image dense matching has become one of the widely used means for DSM generation due to its good performance in both accuracy and efficiency. However, for water areas, the most common ground object, accurate disparity estimation is always a challenge to excellent image dense matching methods, as repr...

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Main Authors: Wenhuan Yang, Xin Li, Bo Yang, Yu Fu
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Remote Sensing
Subjects:
dsm
Online Access:https://www.mdpi.com/2072-4292/12/5/870
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spelling doaj-0ed9711234e44e8f9992d2a9ce1d45082020-11-25T03:03:25ZengMDPI AGRemote Sensing2072-42922020-03-0112587010.3390/rs12050870rs12050870A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water AreasWenhuan Yang0Xin Li1Bo Yang2Yu Fu3School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaSystems Engineering Research Institute of China State Shipbuilding Corporation, Beijing 100036, ChinaImage dense matching has become one of the widely used means for DSM generation due to its good performance in both accuracy and efficiency. However, for water areas, the most common ground object, accurate disparity estimation is always a challenge to excellent image dense matching methods, as represented by semi-global matching (SGM), due to the poor texture. For this reason, a great deal of manual editing is always inevitable before practical applications. The main reason for this is the lack of uniqueness of matching primitives, with fixed size and shape, used by those methods. In this paper, we propose a novel DSM generation method, namely semi-global and block matching (SGBM), to achieve accurate disparity and height estimation in water areas by adaptive block matching instead of pixel matching. First, the water blocks are extracted by seed point growth, and an adaptive block matching strategy considering geometrical deformations, called end-block matching (EBM), is adopted to achieve accurate disparity estimation. Then, the disparity of all other pixels beyond these water blocks is obtained by SGM. Last, the median value of height of all pixels within the same block is selected as the final height for this block after forward intersection. Experiments are conducted on ZiYuan-3 (ZY-3) stereo images, and the results show that DSM generated by our method in water areas has high accuracy and visual quality.https://www.mdpi.com/2072-4292/12/5/870stereo matchingblock matchingdsmwater areazy-3
collection DOAJ
language English
format Article
sources DOAJ
author Wenhuan Yang
Xin Li
Bo Yang
Yu Fu
spellingShingle Wenhuan Yang
Xin Li
Bo Yang
Yu Fu
A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas
Remote Sensing
stereo matching
block matching
dsm
water area
zy-3
author_facet Wenhuan Yang
Xin Li
Bo Yang
Yu Fu
author_sort Wenhuan Yang
title A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas
title_short A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas
title_full A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas
title_fullStr A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas
title_full_unstemmed A Novel Stereo Matching Algorithm for Digital Surface Model (DSM) Generation in Water Areas
title_sort novel stereo matching algorithm for digital surface model (dsm) generation in water areas
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-03-01
description Image dense matching has become one of the widely used means for DSM generation due to its good performance in both accuracy and efficiency. However, for water areas, the most common ground object, accurate disparity estimation is always a challenge to excellent image dense matching methods, as represented by semi-global matching (SGM), due to the poor texture. For this reason, a great deal of manual editing is always inevitable before practical applications. The main reason for this is the lack of uniqueness of matching primitives, with fixed size and shape, used by those methods. In this paper, we propose a novel DSM generation method, namely semi-global and block matching (SGBM), to achieve accurate disparity and height estimation in water areas by adaptive block matching instead of pixel matching. First, the water blocks are extracted by seed point growth, and an adaptive block matching strategy considering geometrical deformations, called end-block matching (EBM), is adopted to achieve accurate disparity estimation. Then, the disparity of all other pixels beyond these water blocks is obtained by SGM. Last, the median value of height of all pixels within the same block is selected as the final height for this block after forward intersection. Experiments are conducted on ZiYuan-3 (ZY-3) stereo images, and the results show that DSM generated by our method in water areas has high accuracy and visual quality.
topic stereo matching
block matching
dsm
water area
zy-3
url https://www.mdpi.com/2072-4292/12/5/870
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