Weighted-based Unsupervised Wishart Classification of Fully Polarimetric SAR Image

Yang  Lei; Liu  Wei; Wang  Zhi-Gang

doi:10.3724/SP.J.1146.2007.00950

Volume 30 Issue 12

Jan. 2011

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Article Navigation > Journal of Electronics & Information Technology > 2008 > 30(12): 2827-2830

Yang Lei, Liu Wei, Wang Zhi-Gang. Weighted-based Unsupervised Wishart Classification of Fully Polarimetric SAR Image[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2827-2830. doi: 10.3724/SP.J.1146.2007.00950

Citation:

Yang Lei, Liu Wei, Wang Zhi-Gang. Weighted-based Unsupervised Wishart Classification of Fully Polarimetric SAR Image[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2827-2830. doi: 10.3724/SP.J.1146.2007.00950

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Weighted-based Unsupervised Wishart Classification of Fully Polarimetric SAR Image

doi: 10.3724/SP.J.1146.2007.00950

Received Date: 2007-06-15
Rev Recd Date: 2007-09-29
Publish Date: 2008-12-19

Abstract

Abstract

For improving the estimated precision and rationality of the scattering coherency matrixes of the class center of different terrain types among the unsupervised classification based on polarimetric target decomposition and the maximum likelihood classifier based on the complex Wishart distribution, a new method for unsupervised classification of terrain types is proposed in this paper. Through weighted-based calculating coherency matrix of the center of every class, the coherency matrix can better represent the class center because the method well considers the correlation of pixels and the texture information of SAR image. The algorithm is described in detail and the contrastive experiment is done using AIRSAR L band polarimetric images. The experiment result indicates that the classifications accuracy of the method is higher and the iterative speed is faster.
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References(1)

References

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