Ben Ayed Ismail, Mitiche Amar, Belhadj Ziad
Institut National de la Recherche Scientifique, INRS-EMT, 800, de La Gauchetière Ouest, Montréal, QC, H5A 1K6, Canada.
IEEE Trans Pattern Anal Mach Intell. 2005 May;27(5):793-800. doi: 10.1109/TPAMI.2005.106.
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.
本研究的目的是通过活动轮廓和水平集将合成孔径雷达（SAR）图像分割成给定的任意数量的伽马均匀区域。由于存在斑点（可建模为强乘性噪声），SAR图像的分割是一个难题。所提出的算法包括在曲线内部与分割区域之间的显式对应关系内演化简单封闭平面曲线，以最小化一个包含数据与噪声斑点模型的一致性项和一个正则化项的准则。在合成图像和真实图像上均展示了结果。
