TY - JOUR
T1 - Parameter estimation in bayesian high-resolution image reconstruction with multisensors
AU - Molina, Rafael
AU - Vega, Miguel
AU - Abad, Javier
AU - Katsaggelos, Aggelos K.
N1 - Funding Information:
Manuscript received October 15, 2002; revised April 10, 2003. This work was supported by the “Comisión Nacional de Ciencia y Tecnología” under Contract TIC2000-1275. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Mario A. T. Figueiredo. R. Molina and J. Abad are with the Departamento de Ciencias de la Computación e I.A. Universidad de Granada, 18071 Granada, Spain (e-mail: rms@decsai.ugr.es). M. Vega is with the Departamento de Lenguajes y Sistemas Informáticos. Universidad de Granada, 18071 Granada, Spain. A. K. Katsaggelos is with the Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL 60208-3118 USA. Digital Object Identifier 10.1109/TIP.2003.818117
PY - 2003/12
Y1 - 2003/12
N2 - In this paper, we consider the estimation of the unknown parameters for the problem of reconstructing a high-resolution image from multiple undersampled, shifted, degraded frames with subpixel displacement errors. We derive mathematical expressions for the iterative calculation of the maximum likelihood estimate of the unknown parameters given the low resolution observed images. These iterative procedures require the manipulation of block-semi circulant (BSC) matrices, that is block matrices with circulant blocks. We show how these BSC matrices can be easily manipulated in order to calculate the unknown parameters. Finally the proposed method is tested on real and synthetic images.
AB - In this paper, we consider the estimation of the unknown parameters for the problem of reconstructing a high-resolution image from multiple undersampled, shifted, degraded frames with subpixel displacement errors. We derive mathematical expressions for the iterative calculation of the maximum likelihood estimate of the unknown parameters given the low resolution observed images. These iterative procedures require the manipulation of block-semi circulant (BSC) matrices, that is block matrices with circulant blocks. We show how these BSC matrices can be easily manipulated in order to calculate the unknown parameters. Finally the proposed method is tested on real and synthetic images.
KW - Bayesian methods
KW - High-resolution image reconstruction
KW - Parameter estimation
UR - http://www.scopus.com/inward/record.url?scp=10844234123&partnerID=8YFLogxK
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U2 - 10.1109/TIP.2003.818117
DO - 10.1109/TIP.2003.818117
M3 - Article
C2 - 18244719
AN - SCOPUS:10844234123
SN - 1057-7149
VL - 12
SP - 1655
EP - 1667
JO - IEEE Transactions on Image Processing
JF - IEEE Transactions on Image Processing
IS - 12
ER -