DOI QR코드

DOI QR Code

THE FAST TRUNCATED LAGRANGE METHOD FOR IMAGE DEBLURRING WITH ANTIREFLECTIVE BOUNDARY CONDITIONS

  • Oh, SeYoung (Department of Mathematics Chungnam National University) ;
  • Kwon, SunJoo (Innovation Center of Engineering Education Chungnam National University)
  • 투고 : 2017.11.28
  • 심사 : 2018.01.28
  • 발행 : 2018.02.15

초록

In this paper, under the assumption of the symmetry point spread function, antireflective boundary conditions(AR-BCs) are considered in connection with the fast truncated Lagrange(FTL) method. The FTL method is proposed as an image restoration method for large-scale ill-conditioned BTTB(block Toeplitz with Toeplitz block) and BTHHTB(block Toeplitz-plus-Hankel matrix with Toeplitz-plus-Hankel blocks) linear systems([13, 17]). The implementation and efficiency of the FTL method in the AR-BCs are further illustrated. Especially, by employing the AR-BCs, both the continuity of the image and the continuity of its normal derivative are preserved at the boundary. A reconstructed image with less artifacts at the boundary is obtained as a result.

키워드

참고문헌

  1. A. Arico, M. Donatelli, J. Nagy, and S. Serra-Capizzano, The anti-reflective transform and regularization by filtering, Numerical Linear Algebra in Signals, Systems, and control, Lecture Notes in Electrical Engineering 80, Springer Verlag, (2011), 1-21.
  2. A. Arico, M. Donatelli, and S. Serra-Capizzano, Spectral analysis of the antireflective algebra, Linear Alg. and its Appl. 428 (2008), 657-675. SIAM Review 52 (2010), no. 1, 113-147.
  3. M. Christiansen and M. Hanke, Deblurring methods using anti-reflective boundary conditions, SIAM J. Matrix Anal. Appl. 22 (2001), 1204-1221.
  4. M. Donatelli and S. Serra-Capizzano, Anti-reflective boundary conditions and re-blurring, Inverse Problem 21 (2005), 169-182.
  5. M. Donatelli, C. Estatico, and S. Serra-Capizzano, Boundary conditions and multiple-image re-blurring: The LBT case, J. of Comp. and Appl. Math. 198 (2006), 426-442.
  6. M. Donatelli, C. Estatico, A Martinelli, and S. Serra-Capizzano, Improved image deblurring with anti-reflective boundary conditions and re-blurring, Inverse Problem 22 (2006), 2035-2053.
  7. M. Donatelli and N. Mastronardi, Fast deconvolution with approximated PSF by RSTLS with antireflective boundary conditions, J. of Comp. and Appl. Math. 236 (2012), 3992-4005.
  8. M. Donatelli, http://scienzecomo.uninsubria.it/mdonatelli/Software/software.html.
  9. R. C. Gonzalez and R. E. Woods, Digital image processing, Prentice Hall, 2002.
  10. P. C. Hansen, Regularization Tools, (2001), http://www.imm.dtu.dk/pch.
  11. P. C. Hansen, Deconvolution and Regularization with Toeplitz matrices, Numerical Algorithms, 29 (2002), 323-378.
  12. P. C. Hansen, J. G. Nagy, and D. P. O'Leary, Deblurring Images Matrices, Spectra, and Filtering, SIAM, 2006.
  13. G. Landi, A fast truncated Lagrange method for large-scale image restoration problems, Applied Mathematics and Computation 186 (2007), 1075-1082.
  14. K. P. Lee, J. G. Nagy, and L. Perrone, Iterative Methods for Image Restoration: A Matlab Object Oriented Approach, Numerical Algorithms 36 (2004), 73-93.
  15. M. K. Ng, R. H. Chan, and W. C. Tang, A fast algorithm for deblurring models with Neumann boundary conditions, SIAM J. Sci. Comp. 21 (1999), no. 3, 851-866. https://doi.org/10.1137/S1064827598341384
  16. M. K. Ng, W. C. Kwan, Image restoration by cosine transform-based iterative regularization, Applied Mathematics and Computation 160 (2005), 499-515.
  17. S. Y. Oh and S. J. Kwon, A fast Lagrange method for large-scale image restoration problems with reflective boundary condition, J. of Chungcheong Math. Soc. 25 (2012), 367-377.
  18. S. Serra-Cappizzano, A note on antireflectibe boundary conditions and fast deblurring models, SIAM J. Sci. Comp. 25 (1999), no. 4, 851-866.
  19. S. Serra-Capizzano, A note on anti-reflective boundary conditions and fast deblurring models, SIAM J. Sci. Comp. 25 (2003), no. 3, 1307-1325.