报告题目：Statistical Information Theory and Geometry for SAR Image Analysis
报 告 人：Alejandro C. Frery
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 explain 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 an unified manner from a statistical viewpoint using Information Theory and Information Geometry.
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.