Universal Impulse Noise Filter Based on Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Nemanja I. Petrovic and Vladimir Crnojevic",
  title =        "Universal Impulse Noise Filter Based on Genetic
  journal =      "IEEE Transactions on Image Processing",
  year =         "2008",
  volume =       "17",
  pages =        "1109--1120",
  number =       "7",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming, genetic
                 algorithms, image denoising, impulse noise genetic
                 programming, impulse noise model, robust estimators,
                 salt-and-pepper noise, supervised learning algorithm,
                 universal impulse noise filter",
  DOI =          "doi:10.1109/TIP.2008.924388",
  ISSN =         "1057-7149",
  abstract =     "In this paper, we present a novel method for impulse
                 noise filter construction, based on the switching
                 scheme with two cascaded detectors and two
                 corresponding estimators. Genetic programming as a
                 supervised learning algorithm is employed for building
                 two detectors with complementary characteristics. The
                 first detector identifies the majority of noisy pixels.
                 The second detector searches for the remaining noise
                 missed by the first detector, usually hidden in image
                 details or with amplitudes close to its local
                 neighborhood. Both detectors are based on the robust
                 estimators of location and scale-median and MAD. The
                 filter made by the proposed method is capable of
                 effectively suppressing all kinds of impulse noise, in
                 contrast to many existing filters which are specialized
                 only for a particular noise model. In addition, we
                 propose the usage of a new impulse noise model-the
                 mixed impulse noise, which is more realistic and harder
                 to treat than existing impulse noise models. The
                 proposed model is the combination of commonly used
                 noise models: salt-and-pepper and uniform impulse noise
                 models. Simulation results show that the proposed
                 two-stage GP filter produces excellent results and
                 outperforms existing state-of-the-art filters.",
  notes =        "Also known as \cite{4531117},",

Genetic Programming entries for Nemanja Petrovic Vladimir Crnojevic