@article{Salvador2014,
abstract = {A new Bayesian Super-Resolution (SR) image registration and reconstruction method is proposed. The new method utilizes a prior distribution based on a general combination of spatially adaptive, or non-stationary, image filters, which includes an adaptive local strength parameter able to preserve both image edges and textures. With the application of variational techniques, the proposed method allows for the automatic estimation of all problem unknowns. An experimental comparison between state of the art methods and the proposed SR approach has been performed on both synthetic and real images. {\textcopyright} 2014 Elsevier Inc.},
author = {Villena, S. and Vega, M. and Molina, R. and Katsaggelos, A.K.},
doi = {10.1016/j.dsp.2014.05.017},
issn = {10512004},
journal = {Digital Signal Processing},
keywords = {Bayesian methods,Parameter estimation,Super-resolution,Total variation,Variational methods},
month = {sep},
pages = {1--10},
title = {{A non-stationary image prior combination in super-resolution}},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1051200414001882},
volume = {32},
year = {2014}
}

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