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Technical Program

Paper Detail

Paper:	SPTM-P10.12
Session:	Estimation
Time:	Thursday, May 18, 16:30 - 18:30
Presentation:	Poster
Topic:	Signal Processing Theory and Methods: Detection, Estimation, Classification Theory and Applications
Title:	PARAMETER ESTIMATION FOR MULTIVARIATE MIXED POISSON DISTRIBUTIONS
Authors:	Florent Chatelain, ENSEEIHT / IRIT, France; André Ferrari, University of Nice Sophia-Antipolis, France; Jean-Yves Tourneret, ENSEEIHT / IRIT / TéSA, France
Abstract:	Estimating the parameters of multivariate distributions whose densities or masses cannot be expressed in tractable closed-form is a challenging problem. This paper concentrates on a family of such discrete distributions referred to as multivariate mixed Poisson distributions (MMPDs). These distributions are interesting for modeling correlations between adjacent pixels of active and astronomical images. Several estimators of MMPD parameters are investigated. These estimators include a composite likelihood estimator and a non-linear least squares estimator.