A loss function model for the restoration of grey level images

Scandinavian Journal of Statistics

Volumn 24, Issue 1, 1997, Pages 103-114

  Rue, Håvard ^a  

^a NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

Author keywords

Bayesian inference; Image restcration; Loss functions; Markov chain Monte Carlo.

Indexed keywords

EID: 0031521651     PISSN: 03036898     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-9469.t01-1-00051     Document Type: Article

References (9)

1. Besag, J. (1986). On the statistical analysis of dirty pictures (with discussion). J. Roy. Statist. Soc. Ser. B 48, 259-302.
2. Besag, J., Green, P., Higdon, D. & Mengersen, K. (1995). Bayesian computation and stochastic systems (with discussion). Statist. Sci. 10, 3-66.
3. Frigessi, A. & Rue, H. (1995). Bayesian image classification with Baddeley's delta loss. Technical Report Statistics No. 5/1995, Department of Mathematics, The University of Trondheim, Trondheim, Norway.
4. Geman, D. (1990). Random fields and inverse problems in imaging. In Ecole d'ete de probabilites de Saint-Flour XVIII, 1988, P. L. Hennequin (Ed). Lecture Notes in Mathematics, 1427, Springer, Berlin.
5. Geman, D. & Reynolds, G. (1992). Constrained restoration and the recovery of discontinuities. IEEE Trans. Pattern Anal. Machine Intell. 14, 367-383.
6. Geman, S. & Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Machine Intell. 6, 721-741.
7. Geman, S. & McClure, D. E. (1987). Statistical methods for tomographic image reconstruction. Bull. Int. Statist. Inst. Bk. 4, 5-21.
8. Rue, H. (1995). New loss functions in Bayesian imaging. J. Amer. Statist. Assoc. 90, 900-908.
9. Winkler, G. (1995). Image analysis, random fields and dynamic Monte Carlo methods. Springer, Berlin.