Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1655-1667 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Image Processing |
| Volume | 12 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 2003 |
Funding
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: [email protected]). 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
Keywords
- Bayesian methods
- High-resolution image reconstruction
- Parameter estimation
ASJC Scopus subject areas
- Software
- Computer Graphics and Computer-Aided Design