Unsupervised Synthetic Aperture Radar image partitioning using Fisher distributions
نویسندگان
چکیده
A new and fast unsupervised technique for partitioning high resolution Synthetic Aperture Radar (SAR) images into homogeneous regions is proposed. This technique is based on Fisher probability density functions (PDF) of the pixel value fluctuations and on an image model that consists of a patchwork of homogeneous regions with polygonal boundaries. The partition is obtained by minimizing the stochastic complexity of the image. Different strategies for the PDF parameter estimation are analyzed and a fast and robust technique is thus proposed. Finally, the relevance of the proposed approach is demonstrated on high resolution SAR images.
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