Sensors 2008, 8(3), 1704-1711; doi:10.3390/s8031704
Article

Multiscale Unsupervised Segmentation of SAR Imagery Using the Genetic Algorithm

1,2,* email, 1,2 and 3
1 School of Computer Science and Technology, Tianjin University of Technology, Tianjin 300191, P.R. China 2 Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin, 300191, China 3 Nanchang Hangkong University, Nanchang, 330034, China
* Author to whom correspondence should be addressed.
Received: 17 January 2008; Accepted: 25 February 2008 / Published: 12 March 2008
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
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Abstract: A valid unsupervised and multiscale segmentation of synthetic aperture radar(SAR) imagery is proposed by a combination GA-EM of the Expectation Maximization(EM) algorith with the genetic algorithm (GA). The mixture multiscale autoregressive(MMAR) model is introduced to characterize and exploit the scale-to-scale statisticalvariations and statistical variations in the same scale in SAR imagery due to radar speckle,and a segmentation method is given by combining the GA algorithm with the EMalgorithm. This algorithm is capable of selecting the number of components of the modelusing the minimum description length (MDL) criterion. Our approach benefits from theproperties of the Genetic and the EM algorithm by combination of both into a singleprocedure. The population-based stochastic search of the genetic algorithm (GA) exploresthe search space more thoroughly than the EM method. Therefore, our algorithm enablesescaping from local optimal solutions since the algorithm becomes less sensitive to itsinitialization. Some experiment results are given based on our proposed approach, andcompared to that of the EM algorithms. The experiments on the SAR images show that theGA-EM outperforms the EM method.
Keywords: SAR Image; Unsupervised Segmentation; Multiscale; Genetic Algorithms.

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MDPI and ACS Style

Wen, X.-B.; Zhang, H.; Jiang, Z.-T. Multiscale Unsupervised Segmentation of SAR Imagery Using the Genetic Algorithm. Sensors 2008, 8, 1704-1711.

AMA Style

Wen X-B, Zhang H, Jiang Z-T. Multiscale Unsupervised Segmentation of SAR Imagery Using the Genetic Algorithm. Sensors. 2008; 8(3):1704-1711.

Chicago/Turabian Style

Wen, Xian-Bin; Zhang, Hua; Jiang, Ze-Tao. 2008. "Multiscale Unsupervised Segmentation of SAR Imagery Using the Genetic Algorithm." Sensors 8, no. 3: 1704-1711.

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