Removal of Mixed Impulse noise and Gaussian noise using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Aher:2012:ICSP,

• 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 details.",
• 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

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