Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images

Accurate geopositioning of optical satellite imagery is a fundamental step for many photogrammetric applications. Considering the imaging principle and data processing manner, SAR satellites can achieve high geopositioning accuracy. Therefore, SAR data can be a reliable source for providing control...

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Main Authors: Zhongli Fan, Li Zhang, Yuxuan Liu, Qingdong Wang, Sisi Zlatanova
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/17/3535
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author Zhongli Fan
Li Zhang
Yuxuan Liu
Qingdong Wang
Sisi Zlatanova
author_facet Zhongli Fan
Li Zhang
Yuxuan Liu
Qingdong Wang
Sisi Zlatanova
author_sort Zhongli Fan
collection DOAJ
description Accurate geopositioning of optical satellite imagery is a fundamental step for many photogrammetric applications. Considering the imaging principle and data processing manner, SAR satellites can achieve high geopositioning accuracy. Therefore, SAR data can be a reliable source for providing control information in the orientation of optical satellite images. This paper proposes a practical solution for an accurate orientation of optical satellite images using SAR reference images to take advantage of the merits of SAR data. Firstly, we propose an accurate and robust multimodal image matching method to match the SAR and optical satellite images. This approach includes the development of a new structural-based multimodal applicable feature descriptor that employs angle-weighted oriented gradients (AWOGs) and the utilization of a three-dimensional phase correlation similarity measure. Secondly, we put forward a general optical satellite imagery orientation framework based on multiple SAR reference images, which uses the matches of the SAR and optical satellite images as virtual control points. A large number of experiments not only demonstrate the superiority of the proposed matching method compared to the state-of-the-art methods but also prove the effectiveness of the proposed orientation framework. In particular, the matching performance is improved by about 17% compared with the latest multimodal image matching method, namely, CFOG, and the geopositioning accuracy of optical satellite images is improved, from more than 200 to around 8 m.
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spelling doaj.art-b28d4de36535492296d615bc9438ec7a2023-11-22T11:10:25ZengMDPI AGRemote Sensing2072-42922021-09-011317353510.3390/rs13173535Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite ImagesZhongli Fan0Li Zhang1Yuxuan Liu2Qingdong Wang3Sisi Zlatanova4Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping (CASM), Beijing 100036, ChinaInstitute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping (CASM), Beijing 100036, ChinaInstitute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping (CASM), Beijing 100036, ChinaInstitute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping (CASM), Beijing 100036, ChinaDepartment of Built Environment, University of New South Wales (UNSW), Sydney 2052, AustraliaAccurate geopositioning of optical satellite imagery is a fundamental step for many photogrammetric applications. Considering the imaging principle and data processing manner, SAR satellites can achieve high geopositioning accuracy. Therefore, SAR data can be a reliable source for providing control information in the orientation of optical satellite images. This paper proposes a practical solution for an accurate orientation of optical satellite images using SAR reference images to take advantage of the merits of SAR data. Firstly, we propose an accurate and robust multimodal image matching method to match the SAR and optical satellite images. This approach includes the development of a new structural-based multimodal applicable feature descriptor that employs angle-weighted oriented gradients (AWOGs) and the utilization of a three-dimensional phase correlation similarity measure. Secondly, we put forward a general optical satellite imagery orientation framework based on multiple SAR reference images, which uses the matches of the SAR and optical satellite images as virtual control points. A large number of experiments not only demonstrate the superiority of the proposed matching method compared to the state-of-the-art methods but also prove the effectiveness of the proposed orientation framework. In particular, the matching performance is improved by about 17% compared with the latest multimodal image matching method, namely, CFOG, and the geopositioning accuracy of optical satellite images is improved, from more than 200 to around 8 m.https://www.mdpi.com/2072-4292/13/17/3535optical satellite imagesSAR imagesmultimodal image matchingimage orientationgeopositioning accuracy improvement
spellingShingle Zhongli Fan
Li Zhang
Yuxuan Liu
Qingdong Wang
Sisi Zlatanova
Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images
Remote Sensing
optical satellite images
SAR images
multimodal image matching
image orientation
geopositioning accuracy improvement
title Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images
title_full Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images
title_fullStr Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images
title_full_unstemmed Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images
title_short Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images
title_sort exploiting high geopositioning accuracy of sar data to obtain accurate geometric orientation of optical satellite images
topic optical satellite images
SAR images
multimodal image matching
image orientation
geopositioning accuracy improvement
url https://www.mdpi.com/2072-4292/13/17/3535
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