Bayesian Image Estimation from an Incomplete Set of Blurred, Undersampled Low Resolution Images

Abstract. This paper deals with the problem of reconstructing a highresolution image from an incomplete set of undersampled, blurred and noisy images shifted with subpixel displacement. We derive mathematical expressions for the calculation of the maximum a posteriori estimate of the high resolution image and the estimation of the parameters involved in the model. We also examine the role played by the prior model when this incomplete set of low resolution images is used. The performance of the method is tested experimentally.

• Type: Conference
• Year: 2003
• Where: IBPRIA
• Authors: Javier Mateos, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
• Keywords: IBPRIA 2003, Image Analysis, Incomplete Set, Resolution Images, Subpixel Displacement