Use of Idempotent Functions in the Aggregation of Different Filters for Noise Removal

  • Luis González-Jaime
  • Mike Nachtegael
  • Etienne Kerre
  • Humberto Bustince
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 214)


The majority of existing denoising algorithms obtain good results for a specific noise model, and when it is known previously. Nonetheless, there is a lack in denoising algorithms that can deal with any unknown noisy images. Therefore, in this paper, we study the use of aggregation functions for denoising purposes, where the noise model is not necessarily known in advance; and how these functions affect the visual and quantitative results of the resultant images.


Denoising Idempotent function Aggregation function OWA operator 



This work is supported by the European Commission under contract no. 238819 (MIBISOC Marie Curie ITN) and by the National Science Foundation of Spain, reference TIN2010-15055.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Luis González-Jaime
    • 1
  • Mike Nachtegael
    • 1
  • Etienne Kerre
    • 1
  • Humberto Bustince
    • 2
  1. 1.Applied Mathematics and Computer ScienceGhent UniversityGhentBelgium
  2. 2.Departamento de Automática y ComputaciónUniversidad Pública de NavarraPamplonaSpain

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