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| An Unsupervised Classification Method of POLINSAR Image Based on Bayesian Information Criterion |
| Yang Wen①② Yan Wei① Tu Shang-tan① Liao Ming-sheng② |
①(School of Electronic Information, Wuhan University, Wuhan 430072, China)
②(State Key Laboratory LIESMARS, Wuhan University, Wuhan 430079, China) |
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Abstract An unsupervised classification algorithm established on the Bayesian Information Criterion (BIC) is presented for Polarimetric and Interferometric SAR (PolInSAR) images. First, an initial classification result is obtained by using Shannon entropy characteristic. Then, the result is optimized by Expectation-Maximization (EM) iteration algorithm and LabelCost optimization algorithm. Meanwhile, the method uses BIC to determine the number of clusters automatically. The experimental results show that the proposed method can not only obtain satisfied classification results, but also automatically determine the number of clusters.
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Received: 19 April 2012
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Corresponding Authors:
Yang Wen
E-mail: yangwen@whu.ecu.cn
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2012, Vol. 34 
