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Multi-Modal Remote Sensing Image Registration Based on Multi-Scale Phase Congruency

机译:基于多尺度相位一致性的多模态遥感图像配准

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Automatic matching of multi-modal remote sensing images remains a challenging task in remote sensing image analysis due to significant non-linear radiometric differences between these images. This paper introduces the phase congruency model with illumination and contrast invariance for image matching, and extends the model to a novel image registration method, named as multi-scale phase consistency (MS-PC). The Euclidean distance between MS-PC descriptors is used as similarity metric to achieve correspondences. The proposed method is evaluated with four pairs of multi-model remote sensing images. The experimental results show that MS-PC is more robust to the radiation differences between images, and performs better than two popular method (i.e. SIFT and SAR-SIFT) in both registration accuracy and tie points number.
机译:由于多模式遥感影像之间的显着非线性辐射差异,因此自动匹配多模式遥感影像仍然是一项艰巨的任务。本文介绍了具有光照和对比度不变性的相位一致性模型用于图像匹配,并将该模型扩展到一种新颖的图像配准方法,即多尺度相位一致性(MS-PC)。 MS-PC描述符之间的欧几里得距离用作相似度,以实现对应关系。该方法通过四对多模型遥感图像进行评估。实验结果表明,MS-PC对图像之间的辐射差异具有更强的鲁棒性,并且在配准精度和联系点数方面均优于两种流行的方法(即SIFT和SAR-SIFT)。

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