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Total Variation Regularization Algorithms for Images Corrupted with Different Noise Models : A Review
Author
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-07-24
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Engineering Sciences and Information Technology
Information Technology and Computer Science
Abstract EN
Total Variation (TV) regularization has evolved from an image denoising method for images corrupted with Gaussian noise into a more general technique for inverse problems such as deblurring, blind deconvolution, and inpainting, which also encompasses the Impulse, Poisson, Speckle, and mixed noise models.
This paper focuses on giving a summary of the most relevant TV numerical algorithms for solving the restoration problem for grayscale/color images corrupted with several noise models, that is, Gaussian, Salt & Pepper, Poisson, and Speckle (Gamma) noise models as well as for the mixed noise scenarios, such the mixed Gaussian and impulse model.
We also include the description of the maximum a posteriori (MAP) estimator for each model as well as a summary of general optimization procedures that are typically used to solve the TV problem.
American Psychological Association (APA)
Rodríguez, Paul. 2013. Total Variation Regularization Algorithms for Images Corrupted with Different Noise Models : A Review. Journal of Electrical and Computer Engineering،Vol. 2013, no. 2013, pp.1-18.
https://search.emarefa.net/detail/BIM-455356
Modern Language Association (MLA)
Rodríguez, Paul. Total Variation Regularization Algorithms for Images Corrupted with Different Noise Models : A Review. Journal of Electrical and Computer Engineering No. 2013 (2013), pp.1-18.
https://search.emarefa.net/detail/BIM-455356
American Medical Association (AMA)
Rodríguez, Paul. Total Variation Regularization Algorithms for Images Corrupted with Different Noise Models : A Review. Journal of Electrical and Computer Engineering. 2013. Vol. 2013, no. 2013, pp.1-18.
https://search.emarefa.net/detail/BIM-455356
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-455356