SAR imagery segmentation using probabilistic winner-take-all clustering

This paper applies a recently-developed neural clustering scheme, called 'probabilistic winner-take-all (PWTA)', to image segmentation. Experimental results are presented. These results show that the PWTA clustering scheme significantly outperforms the popular k-means algorithm when both are utilized to segment a synthetic-aperture-radar image representing ship targets in an open-ocean scene.

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