New method for fast detection and removal of impulsive noise using fuzzy metrics

  • Authors:
  • Joan-Gerard Camarena;Valentín Gregori;Samuel Morillas;Guillermo Peris-Fajarnés

  • Affiliations:
  • E.P.S. de Gandia, Departamento de Matemática Aplicada, Universidad Politécnica de Valencia, Grao de Gandia (Valencia), Spain;E.P.S. de Gandia, Departamento de Matemática Aplicada, Universidad Politécnica de Valencia, Grao de Gandia (Valencia), Spain;E.P.S. de Gandia, Departamento de Expresión Gráfica en la Ingeniería, Universidad Politécnica de Valencia, Grao de Gandia (Valencia), Spain;E.P.S. de Gandia, Departamento de Expresión Gráfica en la Ingeniería, Universidad Politécnica de Valencia, Grao de Gandia (Valencia), Spain

  • Venue:
  • ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
  • Year:
  • 2006

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Abstract

A novel approach to impulsive noise detection in color images is introduced. The neighborhood of a central pixel using a fuzzy metric is considered for the fast detection of noisy pixels using a peer group concept. Then, a filter based on a switching scheme between the Arithmetic Mean Filter (AMF) and the identity operation is proposed. The proposed filter reaches a very good balance between noise suppression and detail-preserving outperforming significantly the classical vector filters. The presented approach is faster than recently introduced switching filters based on similar concepts showing a competitive performance.