Optimal Space-Varying Regularization in Iterative Image Restoration

IEEE Transactions on Image Processing

Volumn 3, Issue 3, 1994, Pages 319-324

  Reeves, Stanley J ^a  

^a AUBURN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS; MATHEMATICAL MODELS; MATHEMATICAL TECHNIQUES;

GENERALIZED CROSS VALIDATION; IMAGE RESTORATION; OPTIMAL REGULARIZATION PARAMETER; WIENER FILER;

IMAGE RECONSTRUCTION;

EID: 0028425592     PISSN: 10577149     EISSN: 19410042     Source Type: Journal    
DOI: 10.1109/83.287028     Document Type: Article

References (10)

1. A. N. Tikhonov and V. Y. Arsenin, Solutions of III-Posed Problems. New York: Winston, 1977.
2. A. K. Katsaggelos, J. Biemond, R. M. Mersereau, and R. W. Schafer, “Nonstationary iterative image restoration,” in Proc. 1985 IEEE Int. Conf. Acoust. Speech Signal Processing, pp. 696–699.
3. R. L. Lagendijk, J. Biemond, and D. E. Boekee, “Regularized iterative image restoration with ringing reduction,” IEEE Trans. Acoust. Speech Signal Processing, vol. 36, pp. 1874–1888, Dec. 1988.
4. A. K. Katsaggelos and K. T. Lay, “Simultaneous blur identification and image restoration using the EM algorithm,” in Proc. SPIE Vol. 1199—Visual Commun. Image Processing IV 1989.
5. S. J. Reeves and R. M. Mersereau, “Optimal estimation of the regularization parameter and stabilizing functional for regularized image restoration,” Opt. Eng., vol. 29, pp. 446–454, May 1990.
6. N. P. Galatsanos and A. K. Katsaggelos, “Cross-validation and other criteria for estimating the regularization parameter,” in Proc. 1991 IEEE Int. Conf. Acoust. Speech Signal Processing, pp. 2497–2500.
7. D. A. Girard, “A fast Monte-Carlo cross-validation” procedure for large least squares problems with noisy data,” Numerische Mathematik, no. 56, pp. 1–23, 1989.
8. M. F. Hutchinson, “A stochastic estimator for the trace of the influence matrix for Laplacian smoothing splines,” Commun. Stat.—Simulation Comput., vol. 18, no. 3, pp. 1059–1076, 1989.
9. S. J. Reeves and R. M. Mersereau, “Optimal regularization parameter estimation for image restoration,” in Proc. SPIE Vol. 1452—Image Processing Algorithms Techn. II, 1991, pp. 127–138.
10. B. R. Hunt, “The application of constrained least-squares estimation to image restoration by digital computer,” IEEE Trans. Comput., vol. C-22, pp. 805–812, Sept. 1973.