An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery
An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery
复制标题
一种集成全局SRTM和图像分割的多源卫星图像匹配算法
DOI：
10.3390/rs8080672
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发表时间：
2016-08-01
期刊：
影响因子：
5
通讯作者：
Chen, Zhipeng
中科院分区：
文献类型：
--
作者：
Ling, Xiao;Zhang, Yongjun;Chen, Zhipeng
提出了一种新的多源卫星图像匹配方法，该方法将全球航天飞机雷达地形使命（SRTM）数据与图像分割相结合，实现了鲁棒的多源匹配。该方法首先利用全球SRTM数据生成核线作为几何约束，然后选择和匹配种子点。为了产生更可靠的匹配结果，本文提出了一种基于区域分割的匹配传播，其中区域分割提取的图像分割，并被认为是一个空间约束。此外，一个相似性度量集成距离，角度和归一化互相关（DANCC），它考虑了几何相似性和辐射相似性，被引入到寻找最佳的对应。利用资源三号卫星、测绘一号卫星、SPOT五号卫星和Google Earth等典型卫星影像进行的实验表明，该方法能够得到可靠、准确的匹配结果。
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.