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
ICNAAM 2010, Numerical Analysis and Applied Mathematics, International Conference 2010
1281
1043
1046
4
978-0-7354-0834-0
Sì, ma tipo non specificato
Affine Scaling
Newton methods
Barzilai-Borwein methods
Image Restoration
1
none
Chan, Raymond H.; Morini, Benedetta; Porcelli, Margherita
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/291176
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