DocumentCode :
1359623
Title :
Multidimensional image reconstruction in astronomy
Author :
Kamalabadi, Farzad
Author_Institution :
Univ. of Illinois, Urbana, IL, USA
Volume :
27
Issue :
1
fYear :
2010
Firstpage :
86
Lastpage :
96
Abstract :
The goal of this article is to describe a unified approach based on the assumption of additive Gaussian noise and regularization theory that illustrates the flavor of such multidimensional image reconstruction problems and the associated challenges. Efficient iterative methods are described for the solution of these problems. Indeed, a crucial point in the solution to the problems considered in this article is the size of the data set and the need for efficient algorithms.
Keywords :
AWGN; astronomical image processing; image reconstruction; iterative methods; additive Gaussian noise; astronomical image reconstruction; data set size; image formation problems; image reconstruction problems; iterative methods; multidimensional image reconstruction; regularisation theory; Astronomy; Atmosphere; Extraterrestrial measurements; Image reconstruction; Inverse problems; Multidimensional systems; Optical imaging; Plasma density; Plasma measurements; Space technology;
fLanguage :
English
Journal_Title :
Signal Processing Magazine, IEEE
Publisher :
ieee
ISSN :
1053-5888
Type :
jour
DOI :
10.1109/MSP.2009.934717
Filename :
5355499
Link To Document :
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