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Remote Sens. 2016, 8(8), 672; doi:10.3390/rs8080672

An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

1
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
2
2012 Laboratory of HUAWEI Technology Co., Ltd., Shenzhen 518000, China
*
Author to whom correspondence should be addressed.
Academic Editors: Naser El-Sheimy, Zahra Lari, Adel Moussa, Xiaofeng Li and Prasad S. Thenkabail
Received: 7 May 2016 / Revised: 9 August 2016 / Accepted: 16 August 2016 / Published: 19 August 2016
(This article belongs to the Special Issue Multi-Sensor and Multi-Data Integration in Remote Sensing)
View Full-Text   |   Download PDF [8605 KB, uploaded 19 August 2016]   |  

Abstract

This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM) data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC), which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3), Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results. View Full-Text
Keywords: image matching; multi-source satellite imagery; epipolar line constraint; SRTM; image segmentation; matching propagation image matching; multi-source satellite imagery; epipolar line constraint; SRTM; image segmentation; matching propagation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Ling, X.; Zhang, Y.; Xiong, J.; Huang, X.; Chen, Z. An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery. Remote Sens. 2016, 8, 672.

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