TY - JOUR
T1 - A bayesian super-resolution approach to demosaicing of blurred images
AU - Vega, Miguel
AU - Molina, Rafael
AU - Katsaggelos, Aggelos K.
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2006
Y1 - 2006
N2 - Most of the available digital color cameras use a single image sensor with a color filter array (CFA) in acquiring an image. In order to produce a visible color image, a demosaicing process must be applied, which produces undesirable artifacts. An additional problem appears when the observed color image is also blurred. This paper addresses the problem of deconvolving color images observed with a single coupled charged device (CCD)from the super-resolution point of view. Utilizing the Bayesian paradigm, an estimate of the reconstructed image and the model parameters is generated. The proposed method is tested on real images.
AB - Most of the available digital color cameras use a single image sensor with a color filter array (CFA) in acquiring an image. In order to produce a visible color image, a demosaicing process must be applied, which produces undesirable artifacts. An additional problem appears when the observed color image is also blurred. This paper addresses the problem of deconvolving color images observed with a single coupled charged device (CCD)from the super-resolution point of view. Utilizing the Bayesian paradigm, an estimate of the reconstructed image and the model parameters is generated. The proposed method is tested on real images.
UR - http://www.scopus.com/inward/record.url?scp=33746593359&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33746593359&partnerID=8YFLogxK
U2 - 10.1155/ASP/2006/25072
DO - 10.1155/ASP/2006/25072
M3 - Article
AN - SCOPUS:33746593359
VL - 2006
JO - Eurasip Journal on Advances in Signal Processing
JF - Eurasip Journal on Advances in Signal Processing
SN - 1687-6172
M1 - 25072
ER -