Bayesian parameter estimation in image reconstruction from subsampled blurred observations

In this paper we consider the estimation of the unknown hyperparameters for the problem of reconstructing a high-resolution image from multiple undersampled, shifted, blurred and degraded frames with subpixel displacement errors. We derive mathematical expressions for the iterative calculation of the maximum likelihood estimate (mle) of the unknown hyperparameters given the low resolution observed images. Finally, the proposed method is tested on a synthetic image.

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: Miguel Vega, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos
• Keywords: ICIP 2003, Image Processing, Maximum Likelihood Estimate, Resolution Observed Images, Subpixel Displacement Errors, Unknown Hyperparameters