Cosine transform preconditioners for high resolution image reconstruction

Linear Algebra and Its Applications

Volumn 316, Issue 1-3, 2000, Pages 89-104

  Ng, Michael K ^c   Chan, Raymond H ^a   Chan, Tony F ^b   Yip, Andy M ^c  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c NONE

Author keywords

Discrete cosine transform; Image reconstruction; Neumann boundary condition; Toeplitz matrix

Indexed keywords

EID: 0034415728     PISSN: 00243795     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0024-3795(99)00274-8     Document Type: Article

References (21)

1. M. Banham, A. Katsaggelos, Digital image restoration, IEEE Signal Processing Magazine, March 1997, pp. 24-41.
2. E. Boman, Fast algorithms for Toeplitz equations, Ph.D. thesis, University of Connecticut, Storrs, CT, October 1993.
3. Boman E., Koltracht I. Fast transform based preconditioners for toeplitz equations. SIAM J. Matrix Anal. Appl. 16:1995;628-645.
4. N. Bose, K. Boo, High-resolution image reconstruction with multisensors, Internat. J. Imaging Systems Technol. 9 (1998) 294-304.
5. Buckley M. Fast computation of a discretized thin-plate smoothing spline for image data. Biometrika. 81:1994;247-258.
6. R. Chan, T. Chan, M. Ng, W. Tang, C. Wong, Preconditioned iterative methods for high-resolution image reconstruction with multisensors, in: F. Luk (Ed.), Proceedings of the SPIE Symposium on Advanced Signal Processing: Algorithms, Architectures, and Implementations, vol. 3461, San Diego CA, July, 1998.
7. R. Chan, T. Chan, C. Wong, Cosine transform based preconditioners for total variation minimization problems in image processing, in: S. Margenov, P. Vassilevski (Eds.), Iterative Methods in Linear Algebra, II, V3, IMACS Series in Computational and Applied Mathematics, Proceedings of the Second IMACS International Symposium on Iterative Methods in Linear Algebra, Bulgaria, June, 1995, pp. 311-329.
8. Chan R., Ng M. Conjugate gradient method for toeplitz system. SIAM Review. 38:1996;427-482.
9. Chan R., Ng M., Wong C. Sine transform based preconditioners for symmetric Toeplitz systems. Linear Algebra Appl. 232:1996;237-260.
10. G. Golub, C. Van Loan, Matrix Computations, third ed., Johns Hopkins University Press, Baltimore, MD, 1996.
11. Kalouptsidis N., Carayannis G., Manolakis D. Fast algorithms for block Toeplitz matrices with Toeplitz entries. Signal Processing. 6:1984;77-81.
12. E. Kaltenbacher, R. Hardie, High resolution infrared image reconstruction using multiple, low resolution, aliased frames, in: Proceedings of the IEEE 1996 National Aerospace and Electronic Conference on NAECON, vol. 2, 1996, pp. 702-709.
13. R. Lagendijk, J. Biemond, Iterative identification and restoration of images, Kluwer Academic Publishers, Dordrecht, 1991.
14. J. Lim, Two-dimensional Signal and Image Processing, Prentice-Hall, Englewood Cliffs, NJ, 1990.
15. F. Luk, D. Vandevoorde, Reducing boundary distortion in image restoration, in: Proceedings of the SPIE 2296, Advanced Signal Processing Algorithms, Architectures and Implementations VI, 1994.
16. Kim S., Bose N., Valenzuela H. Recursive reconstruction of high resolution image from noisy undersampled multiframes. IEEE Trans. Acoust. Speech, and Signal Process. 38(6):1990;1013-1027.
17. M. Ng, R. Chan, W. Tang, A fast algorithm for deblurring models with Neumann boundary conditions, Res. Rept. 99-04, Department of Mathematics, The Chinese University of Hong Kong, SIAM J. Sci. Comput. (to appear).
18. Schultz R., Stevenson R. Extraction of high-resolution frames from video sequences. IEEE Trans. Image Process. 5(6):1996;996-1011.
19. Strang G. The discrete cosine transform. SIAM Review. 41:1999;135-147.
20. A. Tekalp, M. Ozkan, M. Sezan, High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration, in: Proceedings of the IEEE International Conference on Acoustic, Speech, and Signal Processing, III, San Francisco, CA, March 1992, pp. 169-172.
21. Tsai R., Huang T. Multiframe image restoration and registration. Adv. Comput. Vision and Image Process. 1:1984;317-339.