MAP-MRF SUPER-RESOLUTION IMAGE RECONSTRUCTION USING MAXIMUM PSEUDO-LIKELIHOOD PARAMETER ESTIMATION

Autor(es)

Martins, Ana L. D. ; Levada, Alexandre L. M. ; Homem, Murillo R. P. ; Mascarenhas, Nelson D. A. ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: 2008 15TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-5; v. N/A, p. 2-pg., 2009-01-01.

Resumo

In this paper, we address the parameter estimation of a Super-Resolution Image Reconstruction approach following a Maximum a Posteriori Probability (MAP) algorithm. The Generalized Isotropic Multi-Level Logistic (GIMLL) Markov Random Field (MRF) model is considered for the high-resolution image characterization. In most applications, MRF model parameters are still chosen by a trial-and-error procedure through simple manual adjustments. In order to overcome this problem we propose a novel approach based on interval parameter estimation using both the Maximum Pseudo-Likelihood (MPL) technique and an approximation of the asymptotic variance of this estimator. To evaluate the capability of the proposed estimator we used a Markov Chain Monte Carlo algorithm to generate GIMLL model outcomes. The differences between the real parameters and the proposed MPL estimators are not significant. Moreover, the Normalized Mean Square Error (NMSE) of the high-resolution estimations indicate the effectiveness of our approach and the importance of an accurate estimation procedure. (AU)

• Processo FAPESP: 06/01711-4 - Combinação de modelos de campos aleatórios markovianos para classificação contextual de imagens multiespectrais
• Beneficiário: Alexandre Luís Magalhães Levada
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 02/07153-2 - Algoritmos para a reconstrução tomográfica: otimização, restauração, quantificação e aplicação
• Beneficiário: Sergio Shiguemi Furuie
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 04/01632-1 - Super-resolucao de imagens: estudo e desenvolvimento de algoritmos para restauracao de imagens tomograficas e microscopicas.
• Beneficiário: Murillo Rodrigo Petrucelli Homem
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado