Instrument parameter estimation in bayesian convex deconvolution

This paper proposes a Bayesian approach for estimation of instrument parameter in convex image deconvolution. The parameters of the instrument response (PSF) are jointly estimated with the image leading to a myopic deconvolution approach. In addition a special convex field allowing efficient hyperpa...

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Main Authors: Orieux, F, Rodet, T, Giovannelli, J
Format: Conference Proceeding
Language:English
Subjects:
Bayesian methods
convex deconvolution
Deconvolution
Estimation
Instrument parameter estimation
Instruments
Markov processes
Monte-Carlo Markov chain
myopic deconvolution
Noise
Pixel
semi-blind deconvolution
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creator Orieux, F
Rodet, T
Giovannelli, J
description This paper proposes a Bayesian approach for estimation of instrument parameter in convex image deconvolution. The parameters of the instrument response (PSF) are jointly estimated with the image leading to a myopic deconvolution approach. In addition a special convex field allowing efficient hyperparameter estimation is used. The solution is based on a global a posteriori law for unknown parameters and object. The estimate is chosen in the sense of the posterior mean, numerically calculated by means of a Monte-Carlo Markov chain algorithm. The computation is efficient with a partial implementation in Fourier space. Simulation results are provided to assess the effectiveness of the proposed approach.
doi_str_mv 10.1109/ICIP.2010.5651917
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subjects Bayesian methods
convex deconvolution
Deconvolution
Estimation
Instrument parameter estimation
Instruments
Markov processes
Monte-Carlo Markov chain
myopic deconvolution
Noise
Pixel
semi-blind deconvolution
title Instrument parameter estimation in bayesian convex deconvolution
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