Title :
On some Bayesian/regularization methods for image restoration
Author :
Archer, Graeme ; Titterington, D.M.
Author_Institution :
Dept. of Stat., Glasgow Univ., UK
fDate :
7/1/1995 12:00:00 AM
Abstract :
Methods are reviewed for choosing regularized restorations in image processing. In particular, a method developed by Galatsanos and Katsaggelos (see ibid., vol.1, p.322-336, 1992) is given a Bayesian interpretation and is compared with other Bayesian and non-Bayesian alternatives. A small illustrative example is provided and a complement is provided for the discussion of noise variance estimation of Galatsanos et al
Keywords :
Bayes methods; image restoration; maximum likelihood estimation; probability; Bayesian interpretation; Bayesian method; Bayesian/regularization methods; image processing; image restoration; maximum likelihood method; noise variance estimation; noisy images; non-Bayesian method; regularized restorations; Additive noise; Bayesian methods; Helium; Image processing; Image reconstruction; Image restoration; Image sampling; Layout; Pixel; Sampling methods;
Journal_Title :
Image Processing, IEEE Transactions on
