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A new image registration scheme based on curvature scale space curve matching

机译:基于曲率尺度空间曲线匹配的图像配准新方案

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摘要

We propose a new image registration scheme for remote sensing images. This scheme includes three steps in sequence. First, a segmentation process is performed on the input image pair. Then the boundaries of the segmented regions in two images are extracted and matched. These matched regions are called confidence regions. Finally, a nonlinear optimization is performed in the matched regions only to obtain a global set of transform parameters. Experiments show that this scheme is more robust and converges faster than registration of the original image pair. We also develop a new curve-matching algorithm based on curvature scale space to facilitate the second step.
机译:我们提出了一种新的遥感图像配准方案。该方案依次包括三个步骤。首先,对输入图像对执行分割处理。然后,提取并匹配两个图像中的分割区域的边界。这些匹配的区域称为置信区域。最后,仅在匹配区域中执行非线性优化,以获得全局转换参数集。实验表明,该方案比原始图像对的配准更健壮,收敛速度更快。我们还开发了一种基于曲率尺度空间的新曲线匹配算法,以方便进行第二步。

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