文章基本信息

标题：Information theory and image understanding: An application to polarimetric SAR imagery
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作者：Alejandro C. Frery ; Abraão D.C. Nascimento ; Renato J. Cintra 等
期刊名称：Chilean Journal of Statistics
印刷版ISSN：0718-7912
电子版ISSN：0718-7920
出版年度：2011
卷号：2
期号：2
页码：81-99
出版社：Chilean Statistical Society
摘要：This work presents a comprehensive examination of the use of information theory for understanding polarimetric synthetic aperture radar (PolSAR) images by means of contrast measures that can be used as test statistics. Due to the phenomenon called `speckle', common to all images obtained with coherent illumination such as PolSAR imagery, accurate modelling is required in their processing and analysis. The scaled multilook complex Wishart distribution has proven to be a successful approach for modelling radar backscatter from forest and pasture areas. Classication, segmentation, and image analysis techniques, which depend on this model, have been devised, and many of them employ some kind of dissimilarity measure. Specically, we introduce statistical tests for analyzing contrast in such images. These tests are based on the Bhattacharyya, chi-square, Hellinger, Kullback-Leibler and Renyi distances. Results obtained by Monte Carlo experiments reveal the Kullback-Leibler distance as the best one with respect to the empirical test sizes under several situations which include pure and contaminated data. The proposed methodology is applied to actual data, obtained by an E-SAR sensor over surroundings of Weling, Bavaria, Germany.
关键词：Asymptotic theory Hermitian random matrix Hypothesis tests; PolSAR image Signal processing Statistical information theory.-pow