EURASIP Journal on Applied Signal Processing 
Volume 2006 (2006), Article ID 25072, 12 pages
doi:10.1155/ASP/2006/25072

A Bayesian Super-Resolution Approach to Demosaicing of Blurred Images

Miguel Vega,1 Rafael Molina,2 and Aggelos K. Katsaggelos3

 1Departamento de Lenguajes y Sistemas Informáticos, Escuela Técnica Superior de Ingeniería Infomática, Universidad de Granada, Granada 18071, Spain
2Departamento de Ciencias de la Computación e Inteligencia Artificial, Escuela Técnica Superior de Ingeniería Infomática, Universidad de Granada, Granada 18071, Spain
3Department of Electrical Engineering and Computer Science, Robert R. McCormick School of Engineering and Applied Science, Northwestern University, Evanston 60208-3118, IL, USA
Received 10 December 2004; Revised 6 May 2005; Accepted 18 May 2005

Abstract

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.