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

Song Cui, Yanfei Zhong
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引用次数: 6

Abstract

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.
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基于多尺度相位一致性的多模态遥感图像配准
由于多模态遥感图像之间存在显著的非线性辐射差异,多模态遥感图像的自动匹配一直是遥感图像分析中的一个难点。本文引入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,并将该模型扩展为一种新的图像配准方法,称为多尺度相位一致性(MS-PC)。采用MS-PC描述符之间的欧几里得距离作为相似性度量来实现对应。利用四对多模型遥感图像对该方法进行了评价。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,在配准精度和结合点数量上都优于常用的两种方法(SIFT和SAR-SIFT)。
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