All-pixels Participated Image Matching Algorithm for Geometric Solution
The purpose of geometric matching is to extract the geometric transformation parameters between the corresponding images. It is widely used in photogrammetric mapping, deformation detection, and flying platform's posture analysis, etc. In this paper, a new image matching method which is differe...
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doaj-a7c369bbc9c64f45bae9d1eaaf1cef332020-11-24T22:36:37ZzhoSurveying and Mapping PressActa Geodaetica et Cartographica Sinica1001-15951001-15952017-05-0146557358210.11947/j.AGCS.2017.2016036820170520160368All-pixels Participated Image Matching Algorithm for Geometric SolutionYANG Ying0LIN Zongjian1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaThe purpose of geometric matching is to extract the geometric transformation parameters between the corresponding images. It is widely used in photogrammetric mapping, deformation detection, and flying platform's posture analysis, etc. In this paper, a new image matching method which is different from the traditional features based image matching algorithm is proposed, it takes all the pixels of the corresponding images to participate the matching procedure and calculate the geometric parameters by least square criterion. The principle of the algorithm, including the gray corresponding equation, the information quantity inequation and procedure of least square solution are expressed. Particularly, the wavelet analysis for gray signal and calculating the information quantity by signal to noise ratio are discussed in detail. For verifying the theory and algorithm, a series of sequential images taking from a video camera mounted on a helicopter are selected for experiment. The results of two typical models according to the relative orientation elements model and parallax grid model are given, and the experimental results show that the proposed algorithm is feasible and effective. The comparison of APM with ordinary features based method by the information quantity inequation is given in the conclusion.http://html.rhhz.net/CHXB/html/2017-5-573.htmgeometric image matchinginformation theorywavelet analysisgray corresponding equationInformation quantity inequationall-pixels participated matching |
collection |
DOAJ |
language |
zho |
format |
Article |
sources |
DOAJ |
author |
YANG Ying LIN Zongjian |
spellingShingle |
YANG Ying LIN Zongjian All-pixels Participated Image Matching Algorithm for Geometric Solution Acta Geodaetica et Cartographica Sinica geometric image matching information theory wavelet analysis gray corresponding equation Information quantity inequation all-pixels participated matching |
author_facet |
YANG Ying LIN Zongjian |
author_sort |
YANG Ying |
title |
All-pixels Participated Image Matching Algorithm for Geometric Solution |
title_short |
All-pixels Participated Image Matching Algorithm for Geometric Solution |
title_full |
All-pixels Participated Image Matching Algorithm for Geometric Solution |
title_fullStr |
All-pixels Participated Image Matching Algorithm for Geometric Solution |
title_full_unstemmed |
All-pixels Participated Image Matching Algorithm for Geometric Solution |
title_sort |
all-pixels participated image matching algorithm for geometric solution |
publisher |
Surveying and Mapping Press |
series |
Acta Geodaetica et Cartographica Sinica |
issn |
1001-1595 1001-1595 |
publishDate |
2017-05-01 |
description |
The purpose of geometric matching is to extract the geometric transformation parameters between the corresponding images. It is widely used in photogrammetric mapping, deformation detection, and flying platform's posture analysis, etc. In this paper, a new image matching method which is different from the traditional features based image matching algorithm is proposed, it takes all the pixels of the corresponding images to participate the matching procedure and calculate the geometric parameters by least square criterion. The principle of the algorithm, including the gray corresponding equation, the information quantity inequation and procedure of least square solution are expressed. Particularly, the wavelet analysis for gray signal and calculating the information quantity by signal to noise ratio are discussed in detail. For verifying the theory and algorithm, a series of sequential images taking from a video camera mounted on a helicopter are selected for experiment. The results of two typical models according to the relative orientation elements model and parallax grid model are given, and the experimental results show that the proposed algorithm is feasible and effective. The comparison of APM with ordinary features based method by the information quantity inequation is given in the conclusion. |
topic |
geometric image matching information theory wavelet analysis gray corresponding equation Information quantity inequation all-pixels participated matching |
url |
http://html.rhhz.net/CHXB/html/2017-5-573.htm |
work_keys_str_mv |
AT yangying allpixelsparticipatedimagematchingalgorithmforgeometricsolution AT linzongjian allpixelsparticipatedimagematchingalgorithmforgeometricsolution |
_version_ |
1725719397211832320 |