An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery
| Autor: | Xu Huang, Xiao Ling, Chen Zhipeng, Yongjun Zhang, Jinxin Xiong |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Normalization (statistics)
Matching (statistics) Similarity (geometry) 010504 meteorology & atmospheric sciences Computer science Epipolar geometry 0211 other engineering and technologies Scale-space segmentation image matching 02 engineering and technology Shuttle Radar Topography Mission Similarity measure 01 natural sciences multi-source satellite imagery SRTM Segmentation Computer vision Satellite imagery lcsh:Science image segmentation 021101 geological & geomatics engineering 0105 earth and related environmental sciences business.industry epipolar line constraint matching propagation Pattern recognition Image segmentation Computer Science::Computer Vision and Pattern Recognition General Earth and Planetary Sciences lcsh:Q Artificial intelligence business |
| Zdroj: | Remote Sensing; Volume 8; Issue 8; Pages: 672 Remote Sensing, Vol 8, Iss 8, p 672 (2016) |
| ISSN: | 2072-4292 |
| DOI: | 10.3390/rs8080672 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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