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

  • Authors:

  • Abdul Majid;Choong-Hwan Lee;Muhammad Tariq Mahmood;Tae-Sun Choi

  • Affiliations:

  • Pakistan Institute of Engineering and Applied Sciences, Department of Information and Computer Sciences, Nilore, Islamabad, Pakistan and Gwangju Institute of Science and Technology, School of Info ...;Digital Aria Co., Ltd., Visual Information Processing Laboratory, 6, Jungja-dong, Bundang-gu, 463-811, Seongnam-si, Gyenggi-do, Korea;Korea University of Technology and Education, School of Computer Science and Engineering, 1600 Chungjeolno, Byeogchunmyun, 330-708, Cheonan, Chungnam, Korea;Gwangju Institute of Science and Technology, School of Information and Mechatronics, 261 Cheomdan Gwagiro, Buk-Gu, 500-712, Gwangju, Korea

  • Venue:
  • Knowledge and Information Systems
  • Year:
  • 2012

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Abstract

Generally, the impulse noise filtering schemes use all pixels within a neighborhood and increase the size of neighborhood with the increase in noise density. However, the estimate from all pixels within neighborhood 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 emphasizes on few noise-free pixels and small neighborhood. The proposed scheme searches noise-free pixels within a small neighborhood. 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.