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Published in:
2009 | OriginalPaper | Chapter
Parameter Estimation in Bayesian Super-Resolution Image Reconstruction from Low Resolution Rotated and Translated Images
Authors : Salvador Villena, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
Published in: Advanced Concepts for Intelligent Vision Systems
Publisher: Springer Berlin Heidelberg
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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.