Application of Singular Value Decomposition to Tie Points Detection in InSAR Block
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摘要: 该文针对干涉合成孔径雷达(Interferometric Synthetic Aperture Radar, InSAR)区域网连接点(Tie Points, TPs)检测问题，提出一种基于奇异值分解(Singular Value Decomposition, SVD)的检测方法。其核心思想是：为每个特征点构建特征描述符，针对特征描述符的相异性度量距离按一定的相似性分布构建相似性分布矩阵，再由相似性分布矩阵的SVD建立匹配矩阵，并结合匹配矩阵次大值和最大值比值实现TPs检测。该算法具有快速、简单、操作性强等特点。对不同地貌的SAR影像实验验证了该方法的有效性。Abstract: A method based on Singular Value Decomposition (SVD) is presented to solve Tie Points (TPs) detection in Interferometric Synthetic Aperture Radar (InSAR) block. The core concept is to construct a corresponding matrix through SVD of the dissimilar distribution matrix which characterizes the dissimilarity distribution of two descriptors attached to each feature point. The method benefits TPs detection based on combining the corresponding matrix with the ratio of the second greatest value to the greatest one. The algorithm has advantages of high speed, simplicity and technical feasibility. The effectiveness of proposed method is validated by experiments on three adjacent synthetic aperture radar image-pairs of different kinds of terrain.
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