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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 48, Iss. 7 — Mar. 1, 2009
  • pp: 1389–1401

Regularizing active set method for nonnegatively constrained ill-posed multichannel image restoration problem

Yanfei Wang, Jingjie Cao, Yaxiang Yuan, Changchun Yang, and Naihua Xiu  »View Author Affiliations


Applied Optics, Vol. 48, Issue 7, pp. 1389-1401 (2009)
http://dx.doi.org/10.1364/AO.48.001389


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Abstract

In this paper, we consider the nonnegatively constrained multichannel image deblurring problem and propose regularizing active set methods for numerical restoration. For image deblurring problems, it is reasonable to solve a regularizing model with nonnegativity constraints because of the physical meaning of the image. We consider a general regularizing l p l q model with nonnegativity constraints. For p and q equaling 2, the model is in a convex quadratic form, therefore, the active set method is proposed since the nonnegativity constraints are imposed naturally. For p and q not equaling 2, we present an active set method with a feasible Newton-conjugate gradient solution technique. Numerical experiments are presented for ill-posed three-channel blurred image restoration problems.

© 2009 Optical Society of America

OCIS Codes
(000.4430) General : Numerical approximation and analysis
(100.1830) Image processing : Deconvolution
(100.3020) Image processing : Image reconstruction-restoration
(100.3190) Image processing : Inverse problems

ToC Category:
Image Processing

History
Original Manuscript: October 9, 2008
Revised Manuscript: January 15, 2009
Manuscript Accepted: January 19, 2009
Published: February 25, 2009

Citation
Yanfei Wang, Jingjie Cao, Yaxiang Yuan, Changchun Yang, and Naihua Xiu, "Regularizing active set method for nonnegatively constrained ill-posed multichannel image restoration problem," Appl. Opt. 48, 1389-1401 (2009)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-48-7-1389


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