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.
杨文, 颜卫, 涂尚坦, 廖明生. 基于贝叶斯信息准则的极化干涉SAR图像非监督分类[J]. 电子与信息学报, 2012, 34(11): 2628-2634.
Yang Wen, Yan Wei, Tu Shang-Tan, Liao Ming-Sheng. An Unsupervised Classification Method of POLINSAR Image Based on Bayesian Information Criterion. , 2012, 34(11): 2628-2634.