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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Analysis of Minute Features in Speckled Imagery with Maximum Likelihood Estimation | EURASIP Journal on Applied Signal Processing 2004 16 2476-2491 2004 Hindawi Publishing Corporation Analysis of Minute Features in Speckled Imagery with Maximum Likelihood Estimation Alejandro C. Frery Departamento de Tecnologia da Informaẹão Universidade Federal de Alagoas Campus A. C. Simoes BR 104 Norte km 14 Bloco 12 Tabuleiro dos Martins 57072-970 Maceió Brazil Em ail frery@tci.ufal.br Francisco Cribari-Neto Departamento de Estatóstica CCEN Universidade Federal de Pernambuco Cidade Universitória 50740-540 Recife Brazil Email cribari@de.ufpe.br Marcelo O. de Souza Departamento de Estatóstica CCEN Universidade Federal de Pernambuco Cidade Universitória 50740-540 Recife Brazil Email szamarcelo@click21.com.br Received 21 August 2003 Revised 18 June 2004 This paper deals with numerical problems arising when performing maximum likelihood parameter estimation in speckled imagery using small samples. The noise that appears in images obtained with coherent illumination as is the case of sonar laser ultrasound-B and synthetic aperture radar is called speckle and it can be assumed neither Gaussian nor additive. The properties of speckle noise are well described by the multiplicative model a statistical framework from which stem several important distributions. Amongst these distributions one is regarded as the universal model for speckled data namely the G0 law. This paper deals with amplitude data so the Ga distribution will be used. The literature reports that techniques for obtaining estimates maximum likelihood based on moments and on order statistics of the parameters of the GA distribution require samples of hundreds even thousands of observations in order to obtain sensible values. This is verified for maximum likelihood estimation and a proposal based on alternate optimization is made to alleviate this situation. The proposal is assessed with real and simulated data showing that the convergence problems are no longer present. A Monte Carlo experiment is devised to
