Evolutionary Design of Robust Noise-Specific Image Filters

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Vasicek:2011:EDoRNIF,
  title =        "Evolutionary Design of Robust Noise-Specific Image
                 Filters",
  author =       "Zdenek Vasicek and Michal Bidlo",
  pages =        "269--276",
  booktitle =    "Proceedings of the 2011 IEEE Congress on Evolutionary
                 Computation",
  year =         "2011",
  editor =       "Alice E. Smith",
  month =        "5-8 " # jun,
  address =      "New Orleans, USA",
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming, 2D signal processing, cartesian
                 genetic programming representation, digital image
                 processing, evolutionary algorithm, evolutionary
                 design, impulse noise, iterative filtering algorithm,
                 noise intensity, noise median filter, nonlinear noise
                 detection, nonnoise pixels, robust noise specific image
                 filter design, image representation, impulse noise,
                 iterative methods, median filters",
  DOI =          "doi:10.1109/CEC.2011.5949628",
  ISSN =         "Pending",
  abstract =     "Evolutionary design has shown as a powerful technique
                 in solving various engineering problems. One of the
                 areas in which this approach succeeds is digital image
                 processing. Impulse noise represents a basic type of
                 non-linear noise typically affecting a single pixel in
                 different regions of the image. In order to eliminate
                 this type noise median filters have usually been
                 applied. However, for higher noise intensity or wide
                 range of the noise values this approach leads to
                 corrupting non-noise pixels as well which results in
                 images that are smudged or lose some details after the
                 filtering process. Therefore, advanced filtering
                 techniques have been developed including a concept of
                 noise detection or iterative filtering algorithms. In
                 case of the high noise intensity, a single filtering
                 step is insufficient to eliminate the noise and obtain
                 a reasonable quality of the filtered image. Therefore,
                 iterative filters have been introduced. In this paper
                 we apply an evolutionary algorithm combined with
                 Cartesian Genetic Programing representation to design
                 image filters for the impulse noise that are able to
                 compete with some of the best conventionally used
                 iterative filters. We consider the concept of noise
                 detection to be designed together with the filter
                 itself by means of the evolutionary algorithm. Finally,
                 it will be shown that if the evolved filter is applied
                 iteratively on the filtered image, a high-quality
                 results can be obtained using lower computational
                 effort of the filtering process in comparison with the
                 conventional iterative filters.",
  notes =        "CEC2011 sponsored by the IEEE Computational
                 Intelligence Society, and previously sponsored by the
                 EPS and the IET.

                 Also known as \cite{5949628}",
}

Genetic Programming entries for Zdenek Vasicek Michal Bidlo

Citations