TV+TV2 Regularization with Nonconvex Sparseness-Inducing Penalty for Image Restoration
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-04
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
In order to restore the high quality image, we propose a compound regularization method which combines a new higher-order extension of total variation (TV+TV2) and a nonconvex sparseness-inducing penalty.
Considering the presence of varying directional features in images, we employ the shearlet transform to preserve the abundant geometrical information of the image.
The nonconvex sparseness-inducing penalty approach increases robustness to noise and image nonsparsity.
In what follows, we present the numerical solution of the proposed model by employing the split Bregman iteration and a novel p-shrinkage operator.
And finally, we perform numerical experiments for image denoising, image deblurring, and image reconstructing from incomplete spectral samples.
The experimental results demonstrate the efficiency of the proposed restoration method for preserving the structure details and the sharp edges of image.
American Psychological Association (APA)
Lu, Chengwu& Huang, Hua. 2014. TV+TV2 Regularization with Nonconvex Sparseness-Inducing Penalty for Image Restoration. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-498305
Modern Language Association (MLA)
Lu, Chengwu& Huang, Hua. TV+TV2 Regularization with Nonconvex Sparseness-Inducing Penalty for Image Restoration. Mathematical Problems in Engineering No. 2014 (2014), pp.1-15.
https://search.emarefa.net/detail/BIM-498305
American Medical Association (AMA)
Lu, Chengwu& Huang, Hua. TV+TV2 Regularization with Nonconvex Sparseness-Inducing Penalty for Image Restoration. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-498305
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-498305