Image Feature Matching Via Parallax Mapping for Close Range Photogrammetric Application
Image feature matching is an important step in close range photogrammetric applications, and implementing a fast, accurate and robust feature-based image matching technique is a challenging task. To solve the problems of traditional image feature matching algorithms, such as their low accuracy and l...
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doaj-3393655145f647b6b4c829c0dfee465b2021-03-30T01:20:57ZengIEEEIEEE Access2169-35362020-01-018326013261610.1109/ACCESS.2020.29737238998251Image Feature Matching Via Parallax Mapping for Close Range Photogrammetric ApplicationYang Dong0https://orcid.org/0000-0001-9323-9675Dazhao Fan1https://orcid.org/0000-0001-7100-8454Qiuhe Ma2https://orcid.org/0000-0002-4810-1316Song Ji3https://orcid.org/0000-0002-3333-319XInstitute of Surveying and Mapping, Information Engineering University, Zhengzhou, ChinaInstitute of Surveying and Mapping, Information Engineering University, Zhengzhou, ChinaInstitute of Surveying and Mapping, Information Engineering University, Zhengzhou, ChinaInstitute of Surveying and Mapping, Information Engineering University, Zhengzhou, ChinaImage feature matching is an important step in close range photogrammetric applications, and implementing a fast, accurate and robust feature-based image matching technique is a challenging task. To solve the problems of traditional image feature matching algorithms, such as their low accuracy and long processing time, we present a parallax mapping-based matching (PMM) method that is able to improve the computation efficiency, accuracy and robustness of feature-based image matching for close range photogrammetric applications. First, the disparity of the initial corresponding points is calculated, and the mismatches are initially removed via local disparity clustering. Then, the local coordinates of the matching points are constrained by an image division grid. To ensure the correctness of the matching points, the fast polynomial transform is used for as a quadratic constraint. The method can extract high accuracy matching points from the original coarse matching points with low accuracy, and also preserve the true matching points to the greatest extent. Using a variety of experimental datasets and current mainstream feature extraction algorithms, we designed and compared commonly used feature-based image matching algorithms. The experimental results show that the proposed method is simple but effective, can meet the real-time calculation requirements, and outperforms the current state-of-the-art methods.https://ieeexplore.ieee.org/document/8998251/Image matchingrejecting mismatchesmotion consistencyparallax mappingpolynomial |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yang Dong Dazhao Fan Qiuhe Ma Song Ji |
spellingShingle |
Yang Dong Dazhao Fan Qiuhe Ma Song Ji Image Feature Matching Via Parallax Mapping for Close Range Photogrammetric Application IEEE Access Image matching rejecting mismatches motion consistency parallax mapping polynomial |
author_facet |
Yang Dong Dazhao Fan Qiuhe Ma Song Ji |
author_sort |
Yang Dong |
title |
Image Feature Matching Via Parallax Mapping for Close Range Photogrammetric Application |
title_short |
Image Feature Matching Via Parallax Mapping for Close Range Photogrammetric Application |
title_full |
Image Feature Matching Via Parallax Mapping for Close Range Photogrammetric Application |
title_fullStr |
Image Feature Matching Via Parallax Mapping for Close Range Photogrammetric Application |
title_full_unstemmed |
Image Feature Matching Via Parallax Mapping for Close Range Photogrammetric Application |
title_sort |
image feature matching via parallax mapping for close range photogrammetric application |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
Image feature matching is an important step in close range photogrammetric applications, and implementing a fast, accurate and robust feature-based image matching technique is a challenging task. To solve the problems of traditional image feature matching algorithms, such as their low accuracy and long processing time, we present a parallax mapping-based matching (PMM) method that is able to improve the computation efficiency, accuracy and robustness of feature-based image matching for close range photogrammetric applications. First, the disparity of the initial corresponding points is calculated, and the mismatches are initially removed via local disparity clustering. Then, the local coordinates of the matching points are constrained by an image division grid. To ensure the correctness of the matching points, the fast polynomial transform is used for as a quadratic constraint. The method can extract high accuracy matching points from the original coarse matching points with low accuracy, and also preserve the true matching points to the greatest extent. Using a variety of experimental datasets and current mainstream feature extraction algorithms, we designed and compared commonly used feature-based image matching algorithms. The experimental results show that the proposed method is simple but effective, can meet the real-time calculation requirements, and outperforms the current state-of-the-art methods. |
topic |
Image matching rejecting mismatches motion consistency parallax mapping polynomial |
url |
https://ieeexplore.ieee.org/document/8998251/ |
work_keys_str_mv |
AT yangdong imagefeaturematchingviaparallaxmappingforcloserangephotogrammetricapplication AT dazhaofan imagefeaturematchingviaparallaxmappingforcloserangephotogrammetricapplication AT qiuhema imagefeaturematchingviaparallaxmappingforcloserangephotogrammetricapplication AT songji imagefeaturematchingviaparallaxmappingforcloserangephotogrammetricapplication |
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1724187229134258176 |