A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression
Joint Authors
Gil-Jiménez, Pedro
Lafuente-Arroyo, Sergio
López-Sastre, Roberto
Maldonado-Bascón, Saturnino
Gómez-Moreno, Hilario
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-17
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
We present a new impulse noise removal technique based on Support Vector Machines (SVM).
Both classification and regression were used to reduce the “salt and pepper” noise found in digital images.
Classification enables identification of noisy pixels, while regression provides a means to determine reconstruction values.
The training vectors necessary for the SVM were generated synthetically in order to maintain control over quality and complexity.
A modified median filter based on a previous noise detection stage and a regression-based filter are presented and compared to other well-known state-of-the-art noise reduction algorithms.
The results show that the filters proposed achieved good results, outperforming other state-of-the-art algorithms for low and medium noise ratios, and were comparable for very highly corrupted images.
American Psychological Association (APA)
Gómez-Moreno, Hilario& Gil-Jiménez, Pedro& Lafuente-Arroyo, Sergio& López-Sastre, Roberto& Maldonado-Bascón, Saturnino. 2014. A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-1051222
Modern Language Association (MLA)
Gómez-Moreno, Hilario…[et al.]. A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression. The Scientific World Journal No. 2014 (2014), pp.1-15.
https://search.emarefa.net/detail/BIM-1051222
American Medical Association (AMA)
Gómez-Moreno, Hilario& Gil-Jiménez, Pedro& Lafuente-Arroyo, Sergio& López-Sastre, Roberto& Maldonado-Bascón, Saturnino. A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-1051222
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1051222