Article ID Journal Published Year Pages File Type
1548504 Progress in Natural Science: Materials International 2009 4 Pages PDF
Abstract

A novel method that hybridizes genetic algorithm (GA) and expectation maximization (EM) algorithm for the classification of synthetic aperture radar (SAR) imagery is proposed by the finite Gaussian mixtures model (GMM) and multiscale autoregressive (MAR) model. This algorithm is capable of improving the global optimality and consistency of the classification performance. The experiments on the SAR images show that the proposed algorithm outperforms the standard EM method significantly in classification accuracy.

Related Topics
Physical Sciences and Engineering Materials Science Electronic, Optical and Magnetic Materials
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