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Multiregion level-set partitioning of synthetic aperture radar images

机译:合成孔径雷达图像的多区域水平集划分

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The purpose of this study is to investigate synthetic aperture radar (SAR) image segmentation into a given but arbitrary number of gamma homogeneous regions via active contours and level sets. The segmentation of SAR images is a difficult problem due to the presence of speckle which can be modeled as strong, multiplicative noise. The proposed algorithm consists of evolving simple closed planar curves within an explicit correspondence between the interiors of curves and regions of segmentation to minimize a criterion containing a term of conformity of data to a speckle model of noise and a term of regularization. Results are shown on both synthetic and real images.
机译:这项研究的目的是研究通过主动轮廓和水平集将合成孔径雷达(SAR)图像分割为给定但任意数量的伽马均匀区域。由于斑点的存在,SAR图像的分割是一个困难的问题,可以将其建模为强大的乘法噪声。所提出的算法包括在曲线内部和分段区域之间的显式对应关系内演化简单的闭合平面曲线,以最小化包含数据与噪声斑点模型的符合性项和正则化项的标准。结果显示在合成图像和真实图像上。

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