Modified Statistically Homogeneous Pixel Selection For Coherence Estimation With Multi-Temporal Insar Images

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)(2016)

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摘要
Statistically Homogeneous Pixels (SHPs) selection is a significant step of multi-temporal interferometric synthetic aperture radar (InSAR) for Distributed Scatterers (DS). A series of studies namely, Anderson-Darling test (AD test) and its variants, have demonstrated their advantages. However, these algorithms have a similar drawback that they put little attention on the spatial amplitude distributions and cost too much time of processing. To solve the problem, this paper proposes a modified statistically homogeneous pixels selection algorithm (MoSHPS). It utilizes the amplitude values to get the prior information of the images through an unsupervised classifier, in order to guide the SHPs selection. It can improve the accuracy for SHPs selection, and promote the computing efficiency. In the end, results on a series of real TerraSAR-X datas, acquired over a Tianjin area, confirm the effectiveness of this algorithm.
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关键词
Statistically homogeneous pixels (SHPs),spatial adaptive algorithm,K-means,Anderson-Darling test (AD test),coherence estimation
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