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Remote sensing image registration with spatial restraint based on moment invariants and fast generalized fuzzy clustering

机译:基于不变矩和快速广义模糊聚类的空间约束遥感图像配准

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Image registration is a key component in remote sensing image processing. In this paper, we present a remote sensing image registration method by incorporating spatial restraint based on moment invariants and fast generalized fuzzy clustering. Seven moment invariants are extracted as features of objects obtained by the fast generalized fuzzy c-means (FGFCM) algorithm. The objects are matched through these features. Then, we detect the keypoints in corresponding matching regions. Through the spatial restraint, the outliers are removed and the correct matches are increased. The proposed algorithm is evaluated on multi-spectral images, multi-temporal images, and multi-sensor images. Extensive experimental studies prove that the proposed algorithm is promising.
机译:图像配准是遥感图像处理中的关键组成部分。本文提出了一种基于矩不变性的空间约束与快速广义模糊聚类相结合的遥感影像配准方法。提取七个不变矩作为通过快速广义模糊c均值(FGFCM)算法获得的对象的特征。通过这些功能对对象进行匹配。然后,我们在相应的匹配区域中检测关键点。通过空间限制,可以消除异常值,并增加正确的匹配项。在多光谱图像,多时间图像和多传感器图像上对提出的算法进行了评估。大量的实验研究证明了该算法是有前途的。

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