DocumentCode :
2002631
Title :
Two Bayesian image restoration algorithms from partially-known blurs
Author :
Galatsanos, Nikolas P. ; Molina, Rafael ; Mesarovic, Vladimir Z.
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
Volume :
2
fYear :
1998
fDate :
4-7 Oct 1998
Firstpage :
93
Abstract :
In this paper we examine the restoration problem when the point-spread function (PSF) of the degradation system, is partially known. For this problem the PSF is assumed to be the sum of a known deterministic and an unknown random component. This problem, has been examined before; however, in most previous works the problem of estimating the parameters that define the restoration, filters was not addressed. In this paper two iterative algorithms that simultaneously restore the image and estimate the parameters of the restoration filter are proposed using evidence analysis (EA) within the hierarchical Bayesian framework. Numerical experiments are presented that test and compare the proposed algorithms
Keywords :
Bayes methods; digital filters; image enhancement; image restoration; iterative methods; optical transfer function; parameter estimation; Bayesian image restoration algorithms; degradation system; evidence analysis; hierarchical Bayesian framework; iterative algorithms; known deterministic component; partially-known blurs; point-spread function; restoration filter; unknown random component; Additive noise; Additive white noise; Bayesian methods; Covariance matrix; Gaussian noise; Image restoration; Laplace equations; Noise generators; Parameter estimation; Yield estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
0-8186-8821-1
Type :
conf
DOI :
10.1109/ICIP.1998.723324
Filename :
723324
Link To Document :
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