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Local Subpixel Coregistration of Interferometric Synthetic Aperture Radar Images Based on Fractal Models

机译:基于分形模型的干涉合成孔径雷达图像局部亚像素配准

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This paper presents a fine coregistration method for synthetic aperture radar (SAR) image processing, such as in InSAR interferogram generation. Under the assumption that SAR images are properly modeled as fractional Brownian motion, relative subpixel offsets between two images can be derived from the statistics of their increments. The method does not require upsampling or cross-correlation, thus allowing for an accurate offset estimation with less computational load. Implemented as a local coregistration procedure, it also provides a nonrigid geometric alignment that nicely follows the topography of the area. Experimental results show that the method gives comparable results to the conventional method, in terms of the accuracy of the generated digital elevation models. In particular, it displays superior accuracy for images with near homogeneous fractal behavior.
机译:本文提出了一种用于合成孔径雷达(SAR)图像处理的精细配准方法,例如在InSAR干涉图生成中。在将SAR图像正确地建模为分数布朗运动的假设下,可以从其增量统计信息中得出两个图像之间的相对子像素偏移。该方法不需要上采样或互相关,因此允许以较少的计算量进行精确的偏移估计。它是作为一种局部配准程序实施的,它还提供了一个非刚性的几何对齐方式,可以很好地跟随该区域的地形。实验结果表明,就生成的数字高程模型的准确性而言,该方法可提供与传统方法相当的结果。特别是,对于具有接近均一的分形行为的图像,它显示出了卓越的准确性。

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