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【学术报告】Statistical Information Theory and Geometry for SAR Image Analysis
日期:2018-10-15 点击:

报告题目:Statistical Information Theory and Geometry for SAR Image Analysis

报告时间:2018年10月19日,星期五,上午10:00-11:00

报告地点:数学楼(原理科楼)112

报告人:Prof. Alejandro C. Frery, Editor-in-chief of IEEE Geoscience and Remote Sensing Letters

报告摘要:

Statistics has a prominent role in SAR - Synthetic Aperture Radar image processing and analysis. More often than not, these data cannot be described by the usual additive Gaussian noise model. Rather than that, a multiplicative signal-dependent model adequately explains the observations. After summarizing the main distributions for both the univariate and multivariate image formats, we present eight seemingly different problems, and how they can be formulated and solved in a unified manner from a statistical viewpoint using Information Theory and Information Geometry.

报告人简介:

Alejandro C. Frery received the B.Sc. degree in Electronic and Electrical Engineering from the University of Mendoza, Argentina. His M.Sc. degree was in Applied Mathematics (Statistics) from the Institute for Pure and Applied Mathematics (IMPA, Brazil) and his Ph.D. degree was in Applied Computing from the National Institute for Space Research (INPE, Brazil). He is currently the leader of LaCCAN - Laboratory of Scientific Computing and Numerical Analysis, Federal University of Alagoas, Maceió, Brazil. Since 2013 he is the Editor-in-Chief of the IEEE Geoscience and Remote Sensing Letters. His research interests are statistical computing and stochastic modeling.

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