S. Villena and M. Vega and R. Molina and A. K. Katsaggelos, “Bayesian Super-Resolution Image Reconstruction using an l1 prior”
Close
@INPROCEEDINGS{,
author = {S. Villena and M. Vega and R. Molina and A. K. Katsaggelos},
title = {Bayesian Super-Resolution Image Reconstruction using an l1 prior},
booktitle = {6th International Symposium on Image and Signal Processing and Analysis (ISPA 2009) Best paper award, Image Processing and Analysis Track},
year = {2009},
editor = {},
volume = {},
pages = {152-157},
month = {},
organization = {},
url = { http://decsai.ugr.es/vip/files/conferences/123.pdf },
annote = {This paper deals with the problem of high-resolution (HR) image reconstruction, from a set of degraded, under-sampled, shifted and rotated images, under the Bayesian paradigm, utilizing a variational approximation. Bayesian methods rely on image models that encapsulate prior image knowledge and avoid the ill-posedness of the image restoration problems. In this paper a new prior based on the l1 norm of vertical and horizontal first order differences of image pixel values is introduced and its parameters are estimated. The estimated HR images are compared with images provided by other HR reconstruction methods.}
}