Removal of Mixed Impulse noise and Gaussian noise using genetic programming

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

  author =       "R. P. Aher and K. C. Jodhanle",
  booktitle =    "Signal Processing (ICSP), 2012 IEEE 11th International
                 Conference on",
  title =        "Removal of Mixed Impulse noise and Gaussian noise
                 using genetic programming",
  year =         "2012",
  volume =       "1",
  pages =        "613--618",
  abstract =     "In this paper, we have put forward a nonlinear
                 filtering method for removing mixed Impulse and
                 Gaussian noise, based on the two step switching scheme.
                 The switching scheme uses two cascaded detectors for
                 detecting the noise and two corresponding estimators
                 which effectively and efficiently filters the noise
                 from the image. A supervised learning algorithm,
                 Genetic programming, is employed for building the two
                 detectors with complementary characteristics. Most of
                 the noisy pixels are identified by the first detector.
                 The remaining noises are searched by the second
                 detector, which is usually hidden in image details or
                 with amplitudes close to its local neighbourhood. Both
                 the detectors designed are based on the robust
                 estimators of location and scale i.e. Median and Median
                 Absolute Deviation (MAD). Unlike many filters which are
                 specialised only for a particular noise model, the
                 proposed filters in this paper are capable of
                 effectively suppressing all kinds of Impulse and
                 Gaussian noise. The proposed two-step Genetic
                 Programming filters removes impulse and Gaussian noise
                 very efficiently, and also preserves the image
  keywords =     "genetic algorithms, genetic programming, Gaussian
                 noise, image denoising, impulse noise, learning
                 (artificial intelligence), nonlinear filters, Gaussian
                 noise, Median Absolute Deviation, cascaded detectors,
                 complementary characteristics, image details, impulse
                 noise, local neighbourhood, noisy pixels, nonlinear
                 filtering method, second detector, supervised learning
                 algorithm, two step switching scheme, alpha trimmed
                 mean estimator, CWM, Gaussian Noise, Impulse noise,
                 Median, Median Absolute Deviation (MAD), Non-Linear
                 filters, Supervised Learning, Switching scheme",
  DOI =          "doi:10.1109/ICoSP.2012.6491563",
  ISSN =         "2164-5221",
  notes =        "Also known as \cite{6491563}",

Genetic Programming entries for R P Aher K C Jodhanle