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Applied Optics

Applied 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)

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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

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

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)

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