Title :
Shape parameter estimation for generalized Gaussian Markov random field models used in MAP image restoration
Author :
Pun, Wai Ho ; Jeffs, Brian D.
Author_Institution :
Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA
fDate :
Oct. 30 1995-Nov. 1 1995
Abstract :
We propose using the generalized Gaussian Markov random field (GGMRF) image model with MAP estimation to solve the problem of restoration for a blurred and noise corrupted image. The restoration algorithm is adapted to specific characteristics of the true image by estimating the GGMRF shape parameter used in computing the MAP estimation. This shape parameter, p, is estimated based on the sample kurtosis of the image. It is shown that higher quality restorations are obtained when the estimated p value is used, rather than some arbitrary choice as other investigators have used.
Keywords :
image restoration; Bayesian approach; GGMRF; MAP image restoration; blurred image; generalized Gaussian Markov random field models; noise corrupted image; sample kurtosis; shape parameter; shape parameter estimation; Bayesian methods; Degradation; Electronic mail; Gaussian noise; Gaussian processes; Image restoration; Markov random fields; Parameter estimation; Shape; Vectors;
Conference_Titel :
Signals, Systems and Computers, 1995. 1995 Conference Record of the Twenty-Ninth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-8186-7370-2
DOI :
10.1109/ACSSC.1995.540942
