Preconditioners for image restoration by reblurring techniques

• Autores: Pietro Dell�Acqua, Marco Donatelli, Claudio Estatico
• Localización: Journal of computational and applied mathematics, ISSN 0377-0427, Vol. 272, Nº 1, 2014, págs. 313-333
• Idioma: inglés
• DOI: 10.1016/j.cam.2013.10.038
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• Resumen

  • It is well known that iterative algorithms for image deblurring that involve the normal equations show usually a slow convergence. A variant of the normal equations which replaces the conjugate transpose AH of the system matrix A with a new matrix is proposed.

    This approach, which is linked with regularization preconditioning theory and reblurring processes, can be applied to a wide set of iterative methods; here we examine Landweber, Steepest descent, Richardson�Lucy and Image Space Reconstruction Algorithm. Several computational tests show that this strategy leads to a significant improvement of the convergence speed of the methods. Moreover it can be naturally combined with other widely used acceleration techniques.