An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations
Joint Authors
Liu, Kui
Su, Benyue
Tan, Jieqing
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-04
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
To avoid the staircase artifacts, an adaptive image denoising model is proposed by the weighted combination of Tikhonov regularization and total variation regularization.
In our model, Tikhonov regularization and total variation regularization can be adaptively selected based on the gradient information of the image.
When the pixels belong to the smooth regions, Tikhonov regularization is adopted, which can eliminate the staircase artifacts.
When the pixels locate at the edges, total variation regularization is selected, which can preserve the edges.
We employ the split Bregman method to solve our model.
Experimental results demonstrate that our model can obtain better performance than those of other models.
American Psychological Association (APA)
Liu, Kui& Tan, Jieqing& Su, Benyue. 2014. An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations. Advances in Multimedia،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-509421
Modern Language Association (MLA)
Liu, Kui…[et al.]. An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations. Advances in Multimedia No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-509421
American Medical Association (AMA)
Liu, Kui& Tan, Jieqing& Su, Benyue. An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations. Advances in Multimedia. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-509421
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-509421