TY - CHAP
T1 - Bayesian image estimation from an incomplete set of blurred, undersampled low resolution images
AU - Mateos, Javier
AU - Vega, Miguel
AU - Molina, Rafael
AU - Katsaggelos, Aggelos K.
PY - 2003
Y1 - 2003
N2 - This paper deals with the problem of reconstructing a high-resolution 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.
AB - This paper deals with the problem of reconstructing a high-resolution 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.
UR - http://www.scopus.com/inward/record.url?scp=35248849432&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=35248849432&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-44871-6_63
DO - 10.1007/978-3-540-44871-6_63
M3 - Chapter
AN - SCOPUS:35248849432
SN - 3540402179
SN - 9783540402176
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 538
EP - 546
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Perales, Francisco Jose
A2 - Campilho, Aurelio J. C.
A2 - Perez, Nicolas Perez
A2 - Perez, Nicolas Perez
PB - Springer Verlag
ER -