Blur in images can be removed by solving a series of box-constrained linear least-squares problems. In this paper, we compare two recent approaches for solving these problems using affine-scaling methods. Both approaches aim at solving a nonlinear system arising from the Karush-Kuhn-Tucker condition. One approach is to identify the active set and update the inactive components of the iterates by using a Newton-like method. The other is to iteratively solve the nonlinear system entry-wise by a Quasi-Newton method.

Affine Scaling Methods for Image Deblurring Problems

Porcelli Margherita
2010

Abstract

Blur in images can be removed by solving a series of box-constrained linear least-squares problems. In this paper, we compare two recent approaches for solving these problems using affine-scaling methods. Both approaches aim at solving a nonlinear system arising from the Karush-Kuhn-Tucker condition. One approach is to identify the active set and update the inactive components of the iterates by using a Newton-like method. The other is to iteratively solve the nonlinear system entry-wise by a Quasi-Newton method.
2010
978-0-7354-0834-0
Affine Scaling
Newton methods
Barzilai-Borwein methods
Image Restoration
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/291176
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? ND
social impact