TY - GEN
T1 - Parameter estimation in bayesian super-resolution image reconstruction from low resolution rotated and translated images
AU - Villena, Salvador
AU - Vega, Miguel
AU - Molina, Rafael
AU - Katsaggelos, Aggelos K.
PY - 2009
Y1 - 2009
N2 - This paper deals with the problem of high-resolution (HR) image reconstruction, from a set of degraded, under-sampled, shifted and rotated images, utilizing the variational approximation within the Bayesian paradigm. The proposed inference procedure requires the calculation of the covariance matrix of the HR image given the LR observations and the unknown hyperparameters of the probabilistic model. Unfortunately the size and complexity of such matrix renders its calculation impossible, and we propose and compare three alternative approximations. The estimated HR images are compared with images provided by other HR reconstruction methods.
AB - This paper deals with the problem of high-resolution (HR) image reconstruction, from a set of degraded, under-sampled, shifted and rotated images, utilizing the variational approximation within the Bayesian paradigm. The proposed inference procedure requires the calculation of the covariance matrix of the HR image given the LR observations and the unknown hyperparameters of the probabilistic model. Unfortunately the size and complexity of such matrix renders its calculation impossible, and we propose and compare three alternative approximations. The estimated HR images are compared with images provided by other HR reconstruction methods.
KW - Bayesian paradigm
KW - Covariance matrix calculation
KW - High resolution images
KW - Variational inference
UR - http://www.scopus.com/inward/record.url?scp=70649112229&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70649112229&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04697-1_18
DO - 10.1007/978-3-642-04697-1_18
M3 - Conference contribution
AN - SCOPUS:70649112229
SN - 3642046967
SN - 9783642046964
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 188
EP - 199
BT - Advanced Concepts for Intelligent Vision Systems - 11th International Conference, ACIVS 2009, Proceedings
T2 - 11th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2009
Y2 - 28 September 2009 through 2 October 2009
ER -