Impulse noise filtering based on noise-free pixels using genetic programming

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@Article{journals/kais/MajidLMC12,
  author =       "Abdul Majid and Choong-Hwan Lee and 
                 M. Tariq Mahmood and Tae-Sun Choi",
  title =        "Impulse noise filtering based on noise-free pixels
                 using genetic programming",
  journal =      "Knowledge and Information Systems",
  year =         "2012",
  volume =       "32",
  number =       "3",
  pages =        "505--526",
  publisher =    "Springer-Verlag",
  language =     "English",
  keywords =     "genetic algorithms, genetic programming, Impulse
                 noise, Image restoration, Noise detection, Noise
                 filtering",
  ISSN =         "0219-1377",
  DOI =          "doi:10.1007/s10115-011-0456-7",
  bibdate =      "2012-08-14",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/kais/kais32.html#MajidLMC12",
  size =         "22 pages",
  abstract =     "Generally, the impulse noise filtering schemes use all
                 pixels within a neighbourhood and increase the size of
                 neighbourhood with the increase in noise density.
                 However, the estimate from all pixels within
                 neighbourhood may not be accurate. Moreover, the larger
                 window may remove edges and fine details as well. In
                 contrast, we propose a novel impulse noise removal
                 scheme that emphasises on few noise-free pixels and
                 small neighbourhood. The proposed scheme searches
                 noise-free pixels within a small neighbourhood. If at
                 least three pixels are not found, then the noisy pixel
                 is left unchanged in current iteration. This iterative
                 process continues until all noisy pixels are replaced
                 with estimated values. In order to estimate the optimal
                 value of the noisy pixel, genetic programming-based
                 estimator is developed. The estimator (function) is
                 composed of useful pixel information and arithmetic
                 functions. Experimental results show that the proposed
                 scheme is capable of removing impulse noise effectively
                 while preserving the fine image details. Especially,
                 our approach has shown effectiveness against high
                 impulse noise density.",
}

Genetic Programming entries for Abdul Majid Choong-Hwan Lee Muhammad Tariq Mahmood Tae Sun Choi

Citations