A hybrid image restoration approach: Using fuzzy punctual kriging and genetic programming

  • Authors:
  • Asmatullah Chaudhry;Asifullah Khan;Asad Ali;Anwar M. Mirza

  • Affiliations:
  • Faculty of Computer Sciences and Engineering, Ghulam Ishaq Khan (GIK) Institute of Engineering Science and Technology, Swabi, Pakistan;Department of Computer and Information Sciences, Pakistan Institute of Engineering and Applied Sciences, Nilore, Pakistan;Faculty of Computer Sciences and Engineering, Ghulam Ishaq Khan (GIK) Institute of Engineering Science and Technology, Swabi, Pakistan;Faculty of Computer Sciences and Engineering, Ghulam Ishaq Khan (GIK) Institute of Engineering Science and Technology, Swabi, Pakistan

  • Venue:
  • International Journal of Imaging Systems and Technology
  • Year:
  • 2007

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Abstract

We present an intelligent technique for image denoising problem of gray level images degraded with Gaussian white noise in spatial domain. The proposed technique consists of using fuzzy logic as a mapping function to decide whether a pixel needs to be krigged or not. Genetic programming is then used to evolve an optimal pixel intensity-estimation function for restoring degraded images. The proposed system has shown considerable improvement when compared both qualitatively and quantitatively with the adaptive Wiener filter, methods based on fuzzy kriging, and a fuzzy-based averaging technique. Experimental results conducted using an image database confirms that the proposed technique offers superior performance in terms of image quality measures. This also validates the use of hybrid techniques for image restoration. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 224–231, 2007