A Bayesian super-resolution approach to demosaicing of blurred images

被引：7
|
作者：
Vega, Miguel [1 ]
Molina, Rafael
Katsaggelos, Aggelos K.
机构：
[1] Univ Granada, Escuela Tecn Super Ingn Informat, Dept Lenguajes & Sistemas Informat, E-18071 Granada, Spain
[2] Univ Granada, Escuela Tecn Super Ingn Informat, Dept Ciencias Computac & Inteligencia Artificial, E-18071 Granada, Spain
[3] Northwestern Univ, Robert R McCormick Sch Engn & Appl Sci, Dept Elect Engn & Comp Sci, Evanston, IL 60208 USA
来源：
EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING | 2006年 / 2006卷 / 1期
关键词：
D O I：
10.1155/ASP/2006/25072
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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. Copyright (C) 2006 Hindawi Publishing Corporation. All rights reserved.
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收藏
页数：12
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