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Fast morphological pyramid matching algorithm based on the Hausdorff distance

机译:基于Hausdorff距离的快速形态学金字塔匹配算法。

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Because the two images used in realistic image matching are generally from the different kinds of sensors, and the physical peculiarity of these images are different, it is very difficult to match the different kinds of images. Aiming at the maching problem between the synthesis aperture radar (SAR) images and the optic images, a fast morphological pyramid matching algorithm based on the Hausdorff distance was proposed. Firstly, in this algorithm edge images were taken as the characteristic space which were extracted respectively from the optic images and the SAR images, and then a distance measurement based on partial mean-Hausdorff distance was adopted as similarity measurement, after that a multiscale flat-structuring elements close-open morphological hybrid pyramid based on the contour bougie (CB) morphology was adopted as the search strategy. This matching algorithm between the real SAR image and optical image was simulated and the results show that it has high matching accuracy and fast computation speed.
机译:由于用于现实图像匹配的两个图像通常来自不同类型的传感器,并且这些图像的物理特性不同,因此很难匹配不同类型的图像。针对合成孔径雷达图像与光学图像之间的匹配问题,提出一种基于Hausdorff距离的快速形态金字塔匹配算法。该算法首先将边缘图像作为特征空间,分别从光学图像和SAR图像中提取特征空间,然后基于偏均值-Hausdorff距离的距离测量作为相似性测量,然后进行多尺度平采用基于轮廓布吉(CB)形态的结构-开-闭形态混合金字塔作为搜索策略。对实际SAR图像和光学图像之间的匹配算法进行了仿真,结果表明,该算法具有较高的匹配精度和较快的计算速度。

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