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The Scientific World Journal
Volume 2014, Article ID 826405, 15 pages
http://dx.doi.org/10.1155/2014/826405
Research Article

A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression

Departamento de Teoría de la Señal y Comunicaciones, Universidad de Alcalá, Alcalá de Henares , 28805 Madrid, Spain

Received 2 May 2014; Revised 9 July 2014; Accepted 24 July 2014; Published 17 August 2014

Academic Editor: Gangyi Jiang

Copyright © 2014 Hilario Gómez-Moreno et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

The following is the list of published articles that have cited the current article.

  • Jayasree, and Narayanan, “An efficient mixed noise removal technique from gray scale images using noisy pixel modification technique,” 2015 International Conference on Communication and Signal Processing, ICCSP 2015, pp. 336–339, 2015. View at Publisher · View at Google Scholar
  • Tai-Hoon Kim, Sudipta Roy, Shayak Sadhu, Samir Kumar Bandyopadhyay, and Debnath Bhattacharyya, “Brain tumor classification using adaptive neuro-fuzzy inference system from MRI,” International Journal of Bio-Science and Bio-Technology, vol. 8, no. 3, pp. 203–218, 2016. View at Publisher · View at Google Scholar
  • Mathias Pelka, Peter Bartmann, Swen Leugner, and Horst Hellbrück, “Minimizing Indoor Localization Errors for Non-Line-of-Sight Propagation,” ICL-GNSS 2018 - 2018 8th International Conference on Localization and GNSS: Seamless Indoor-Outdoor Localization, Proceedings, 2018. View at Publisher · View at Google Scholar