Mean field approximation using compound Gauss-Markov random field for edge detection and image restoration

Author

Zerubia, Josiane ; Challappa, R.

Author_Institution

Signal & Image Processing Inst., Univ. of Southern California, Los Angeles, CA, USA

fYear

1990

fDate

3-6 Apr 1990

Firstpage

2193

Abstract

A composed Gauss-Markov random field (CGMRF) model is used with mean field approximation for edge detection and image restoration. A set of iterative equations is presented for the mean values of the intensity field and both horizontal and vertical line processes. It is shown that if the CGMRF is isotropic, the same equations as those of Geiger and Girosi (1989) are obtained. How the proposed method is related to the graduated nonconvexity technique using CGMRF is shown. From an implementation point of view, the emphasis is on the use of an optimal step-descent method to get a robust algorithm. Edge detection and image restoration results from a noisy image are presented

Keywords

Markov processes; approximation theory; iterative methods; picture processing; signal synthesis; Gauss-Markov random field; edge detection; graduated nonconvexity technique; horizontal line process; image restoration; intensity field; iterative equations; mean field approximation; mean values; noisy image; optimal step-descent method; vertical line process; Equations; Gaussian approximation; Image edge detection; Image processing; Image reconstruction; Image restoration; Noise level; Robustness; Simulated annealing; Surface reconstruction;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.115992

Filename

115992