Application of the partitioning method to specific Toeplitz matrices

Predrag Stanimirović; Marko Miladinović; Igor Stojanović; Sladjana Miljković

International Journal of Applied Mathematics and Computer Science (2013)

  • Volume: 23, Issue: 4, page 809-821
  • ISSN: 1641-876X

Abstract

top
We propose an adaptation of the partitioning method for determination of the Moore-Penrose inverse of a matrix augmented by a block-column matrix. A simplified implementation of the partitioning method on specific Toeplitz matrices is obtained. The idea for observing this type of Toeplitz matrices lies in the fact that they appear in the linear motion blur models in which blurring matrices (representing the convolution kernels) are known in advance. The advantage of the introduced method is a significant reduction in the computational time required to calculate the Moore-Penrose inverse of specific Toeplitz matrices of an arbitrary size. The method is implemented in MATLAB, and illustrative examples are presented.

How to cite

top

Predrag Stanimirović, et al. "Application of the partitioning method to specific Toeplitz matrices." International Journal of Applied Mathematics and Computer Science 23.4 (2013): 809-821. <http://eudml.org/doc/262291>.

@article{PredragStanimirović2013,
abstract = {We propose an adaptation of the partitioning method for determination of the Moore-Penrose inverse of a matrix augmented by a block-column matrix. A simplified implementation of the partitioning method on specific Toeplitz matrices is obtained. The idea for observing this type of Toeplitz matrices lies in the fact that they appear in the linear motion blur models in which blurring matrices (representing the convolution kernels) are known in advance. The advantage of the introduced method is a significant reduction in the computational time required to calculate the Moore-Penrose inverse of specific Toeplitz matrices of an arbitrary size. The method is implemented in MATLAB, and illustrative examples are presented.},
author = {Predrag Stanimirović, Marko Miladinović, Igor Stojanović, Sladjana Miljković},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {Moore-Penrose inverse; partitioning method; Toeplitz matrices; MATLAB; image restoration; MATLAB; numerical examples; convolution kernel},
language = {eng},
number = {4},
pages = {809-821},
title = {Application of the partitioning method to specific Toeplitz matrices},
url = {http://eudml.org/doc/262291},
volume = {23},
year = {2013},
}

TY - JOUR
AU - Predrag Stanimirović
AU - Marko Miladinović
AU - Igor Stojanović
AU - Sladjana Miljković
TI - Application of the partitioning method to specific Toeplitz matrices
JO - International Journal of Applied Mathematics and Computer Science
PY - 2013
VL - 23
IS - 4
SP - 809
EP - 821
AB - We propose an adaptation of the partitioning method for determination of the Moore-Penrose inverse of a matrix augmented by a block-column matrix. A simplified implementation of the partitioning method on specific Toeplitz matrices is obtained. The idea for observing this type of Toeplitz matrices lies in the fact that they appear in the linear motion blur models in which blurring matrices (representing the convolution kernels) are known in advance. The advantage of the introduced method is a significant reduction in the computational time required to calculate the Moore-Penrose inverse of specific Toeplitz matrices of an arbitrary size. The method is implemented in MATLAB, and illustrative examples are presented.
LA - eng
KW - Moore-Penrose inverse; partitioning method; Toeplitz matrices; MATLAB; image restoration; MATLAB; numerical examples; convolution kernel
UR - http://eudml.org/doc/262291
ER -

References

top
  1. Banham, M.R. and Katsaggelos, A.K. (1997). Digital image restoration, IEEE Signal Processing Magazine 14(2): 24-41. 
  2. Ben-Israel, A. and Grevile, T.N.E. (2003). Generalized Inverses, Theory and Applications, Second Edition, Canadian Mathematical Society/Springer, New York, NY. 
  3. Bhimasankaram, P. (1971). On generalized inverses of partitioned matrices, Sankhya: The Indian Journal of Statistics, Series A 33(3): 311-314. Zbl0231.15011
  4. Bovik, A. (2005). Handbook of Image and Video Processing, Elsevier Academic Press, Burlington. Zbl0967.68155
  5. Bovik, A. (2009). The Essential Guide to the Image Processing, Elsevier Academic Press, Burlington. 
  6. Chantas, G.K., Galatsanos, N.P. and Woods, N.A. (2007). Super-resolution based on fast registration and maximum a posteriori reconstruction, IEEE Transactions on Image Processing 16(7): 1821-1830. 
  7. Chountasis, S., Katsikis, V.N. and Pappas, D. (2009a). Applications of the Moore-Penrose inverse in digital image restoration, Mathematical Problems in Engineering 2009, Article ID: 170724, DOI: 10.1155/2010/750352. Zbl1191.68778
  8. Chountasis, S., Katsikis, V.N. and Pappas, D. (2009b). Image restoration via fast computing of the Moore-Penrose inverse matrix, 16th International Conference on Systems, Signals and Image Processing, IWSSIP 2009,Chalkida, Greece, Article number: 5367731. Zbl1191.68778
  9. Chountasis, S., Katsikis, V.N. and Pappas, D. (2010). Digital image reconstruction in the spectral domain utilizing the Moore-Penrose inverse, Mathematical Problems in Engineering 2010, Article ID: 750352, DOI: 10.1155/2010/750352. Zbl1189.94016
  10. Cormen, T.H., Leiserson, C.E., Rivest, R.L. and Stein, C. (2001). Introduction to Algorithms, Second Edition, MIT Press, Cambridge, MA. Zbl1047.68161
  11. Courrieu, P. (2005). Fast computation of Moore-Penrose inverse matrices, Neural Information Processing-Letters and Reviews 8(2): 25-29. 
  12. Craddock, R.C., James, G.A., Holtzheimer, P.E. III, Hu, X.P. and Mayberg, H.S. (2012). A whole brain FMRI atlas generated via spatially constrained spectral clustering, Human Brain Mapping 33(8): 1914-1928. 
  13. Dice, L.R. (1945). Measures of the amount of ecologic association between species, Ecology 26(3): 297-302. 
  14. Górecki, T. and Łuczak, M. (2013). Linear discriminant analysis with a generalization of the Moore-Penrose pseudoinverse, International Journal of Applied Mathematics and Computer Science 23(2): 463-471, DOI: 10.2478/amcs-2013-0035. Zbl06246503
  15. Graybill, F. (1983). Matrices with Applications to Statistics, Second Edition, Wadsworth, Belmont, CA. Zbl0496.15002
  16. Greville, T.N.E. (1960). Some applications of the pseudo-inverse of matrix, SIAM Review 3(1): 15-22. Zbl0168.13303
  17. Hansen, P.C., Nagy, J.G. and O'Leary, D.P. (2006). Deblurring Images: Matrices, Spectra, and Filtering, SIAM, Philadelphia, PA. 
  18. Hillebrand, M. and Muller, C.H. (2007). Outlier robust corner-preserving methods for reconstructing noisy images, The Annals of Statistics 35(1): 132-165. Zbl1114.62050
  19. Hufnagel, R.E. and Stanley, N.R. (1964). Modulation transfer function associated with image transmission through turbulence media, Journal of the Optical Society of America 54(1): 52-60. 
  20. Kalaba, R.E. and Udwadia, F.E. (1993). Associative memory approach to the identification of structural and mechanical systems, Journal of Optimization Theory and Applications 76(2): 207-223. Zbl0791.93019
  21. Kalaba, R.E. and Udwadia, F.E. (1996). Analytical Dynamics: A New Approach, Cambridge University Press, Cambridge. Zbl0875.70100
  22. Karanasios, S. and Pappas, D. (2006). Generalized inverses and special type operator algebras, Facta Universitatis, Mathematics and Informatics Series 21(1): 41-48. Zbl1266.47003
  23. Katsikis, V.N., Pappas, D. and Petralias, A. (2011). An improved method for the computation of the Moore-Penrose inverse matrix, Applied Mathematics and Computation 217(23): 9828-9834. Zbl1220.65049
  24. Katsikis, V. and Pappas, D. (2008). Fast computing of the Moore-Penrose inverse matrix, Electronic Journal of Linear Algebra 17(1): 637-650. Zbl1176.65048
  25. MathWorks (2009). Image Processing Toolbox User's Guide, The Math Works, Inc., Natick, MA. 
  26. MathWorks (2010). MATLAB 7 Mathematics, The Math Works, Inc., Natick, MA. 
  27. Noda, M.T., Makino, I. and Saito, T. (1997). Algebraic methods for computing a generalized inverse, ACM SIGSAM Bulletin 31(3): 51-52. 
  28. Penrose, R. (1956). On a best approximate solution to linear matrix equations, Proceedings of the Cambridge Philosophical Society 52(1): 17-19. Zbl0070.12501
  29. Prasath, V.B.S. (2011). A well-posed multiscale regularization scheme for digital image denoising, International Journal of Applied Mathematics and Computer Science 21(4): 769-777, DOI: 10.2478/v10006-011-0061-7. Zbl1283.68385
  30. Rao, C. (1962). A note on a generalized inverse of a matrix with applications to problems in mathematical statistics, Journal of the Royal Statistical Society, Series B 24(1): 152-158. Zbl0121.14502
  31. Röbenack, K. and Reinschke, K. (2011). On generalized inverses of singular matrix pencils, International Journal of Applied Mathematics and Computer Science 21(1): 161-172, DOI: 10.2478/v10006-011-0012-3. Zbl1221.93096
  32. Schafer, R.W., Mersereau, R.M. and Richards, M.A. (1981). Constrained iterative restoration algorithms, Proceedings of the IEEE 69(4): 432-450. 
  33. Shinozaki, N., Sibuya, M. and Tanabe, K. (1972). Numerical algorithms for the Moore-Penrose inverse of a matrix: Direct methods, Annals of the Institute of Statistical Mathematics 24(1): 193-203. Zbl0315.65027
  34. Smoktunowicz, A. and Wróbel, I. (2012). Numerical aspects of computing the Moore-Penrose inverse of full column rank matrices, BIT Numerical Mathematics 52(2): 503-524. Zbl1251.65053
  35. Stojanović, I., Stanimirović, P. and Miladinović, M. (2012). Applying the algorithm of Lagrange multipliers in digital image restoration, Facta Universitatis, Mathematics and Informatics Series 27(1): 41-50. Zbl1299.68211
  36. Udwadia, F.E. and Kalaba, R.E. (1997). An alternative proof for Greville's formula, Journal of Optimization Theory and Applications 94(1): 23-28. Zbl0893.65020
  37. Udwadia, F.E. and Kalaba, R.E. (1999). General forms for the recursive determination of generalized inverses: Unified approach, Journal of Optimization Theory and Applications 101(3): 509-521. Zbl0946.90117

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.