Model selection criteria for image restoration

IEEE Transactions on Neural Networks

Volumn 20, Issue 8, 2009, Pages 1357-1363

  Seghouane, Abd Krim ^a,b  

^a CSIRO   (Australia)

^b AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

Akaike information criterion (AIC); Bayesian information criterion (BIC); Image restoration; Model selection; Regularization

Indexed keywords

AKAIKE INFORMATION CRITERION (AIC); BAYESIAN INFORMATION CRITERION (BIC); IMAGE RESTORATION; MODEL SELECTION; REGULARIZATION;

BAYESIAN NETWORKS; IMAGE RECONSTRUCTION; PARAMETER ESTIMATION; PHILOSOPHICAL ASPECTS;

RESTORATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; COMPUTER SIMULATION; IMAGE PROCESSING; METHODOLOGY; PROBABILITY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COMPUTER SIMULATION; IMAGE PROCESSING, COMPUTER-ASSISTED; LINEAR MODELS; PATTERN RECOGNITION, AUTOMATED; PROBABILITY;

EID: 68949211719     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2009.2024146     Document Type: Article

References (23)

1. M. R. Banham and A. K. Katsaggelos, "Digital image restoration," IEEE Signal Process. Mag., vol. 14, no. 2, pp. 24-41, Mar. 1997.
2. L. Guan, A. Anderson, and J. Sutton, "A network of networks processing model for image regularization," IEEE Trans. Neural Netw., vol. 8, no. 1, pp. 169-174, Jan. 1997.
3. H. S. Wong and L. Guan, "A neural learning approach for adaptive image restoration using a fuzzy model-based network architecture," IEEE Trans. Neural Netw., vol. 12, no. 3, pp. 516-531, May 2001.
4. R. Molina, A. K. Katsaggelos, and J. Mateos, "Bayesian and regularization methods for hyperparameter estimation in image restoration," IEEE Trans. Image Process., vol. 8, no. 2, pp. 231-246, Feb. 1999.
5. S. W. Perry and L. Guan, "Weight assignment for adaptive image restoration by neural networks," IEEE Trans. Neural Netw., vol. 11, no. 1, pp. 156-170, Jan. 2000.
6. G. Archer and D. M. Titterington, "On some Bayesian/regularization methods for image restoration," IEEE Trans. Image Process., vol. 4, no. 7, pp. 989-995, Jul. 1995.
7. M. G. Kang and A. K. Katsaggelos, "General choice of the regularization functional in regularized image restoration," IEEE Trans. Image Process., vol. 4, no. 5, pp. 594-602, May 1995.
8. B. R. Hunt, "The application of constrained least-squares estimation to image restoration by digital computer," IEEE Trans. Comput., vol. 22, no. 9, pp. 805-812, Sep. 1973.
9. A. M. Thompson, J. C. Brown, J. W. Kay, and D. M. Titterington, "A study of methods of choosing the smoothing parameter in image restoration by regularization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 13, no. 4, pp. 326-339, Apr. 1991.
10. N. P. Galatsanos and A. K. Katsaggelos, "Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation," IEEE Trans. Image Process., vol. 1, no. 3, pp. 322-336, Jul. 1992.
11. N. Fortier, G. Demoment, and Y. Goussard, "GCV and ml methods of determining parameters in image restoration by regularization: Fast computation in the spatial domain and experimental comparison," J. Vis. Commun. Image Represent., vol. 4, pp. 157-170, 1993.
12. A. M. Thompson, J. W. Kay, and D. M. Titterington, "A cautionary note about crossvalidatory choice," J. Statist. Comput. Simulat., vol. 33, pp. 199-216, 1989.
13. H. Akaike, "A new look at the statistical model identification," IEEE Trans. Autom. Control, vol. AC-19, no. 6, pp. 716-723, Dec. 1974.
14. G. Schwarz, "Estimating the dimension of a model," Ann. Statist. vol. 6, pp. 461-464, 1978.
15. R. Shibata, "Statistical aspect of model selection," in From Data to Model, J. C. Willems, Ed. New York: Springer-Verlag, 1989, pp. 215-240.
16. C. M. Hurvich and C. L. Tsai, "Regression and time series model selection in small samples," Biometrika, vol. 76, pp. 297-307, 1989.
17. H. Akaike, Time Series Analysis and Control Through Parametric Models ser. Applied Time Series Analysis, D. F. Findley, Ed. New York: Academic, 1978, pp. 1-23.
18. L. Tierney, R. E. Kass, and J. B. Kadane, "Fully exponential Laplace approximations to expectations and variances of nonpositive functions," J. Amer. Statist. Assoc., vol. 84, pp. 710-716, 1989.
19. A. A. Neath and J. E. Cavanaugh, "Regression and time series model selection using variants of the Schwartz information criterion," Commun. Statist., vol. 26, pp. 559-580, 1997.
20. G. H. Golub, M. Heath, and G. Wahba, "Generalized cross-validation as a method for choosing a good ridge parameter," Technometrics, vol. 21, pp. 215-223, 1979.
21. A. D. R. McQuarie and C. L. Tsai, Regression and Time Series Model Selection. Singapore: World Scientific, 1998.
22. C. Tomasi and R. Manduchi, "Bilateral filtering for gray and color images," in Proc. IEEE Int. Conf. Comput. Vis., Washington, DC, 1998, pp. 839-846.
23. S. Konishi and G. Kitagawa, "Generalized information criteria in model selection," Biometrika, vol. 83, pp. 875-890, 1996.