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Spatially Adaptive Image Restoration Using Fuzzy Punctual Kriging

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Abstract

We present a general formulation based on punctual kriging and fuzzy concepts for image restoration in spatial domain. Gray-level images degraded with Gaussian white noise have been considered. Based on the pixel local neighborhood, fuzzy logic has been employed intelligently to avoid unnecessary estimation of a pixel. The intensity estimation of the selected pixels is then carried out by employing punctual kriging in conjunction with the method of Lagrange multipliers and estimates of local semi-variances. Application of such a hybrid technique performing both selection and intensity estimation of a pixel demonstrates substantial improvement in the image quality as compared to the adaptive Wiener filter and existing fuzzy-kriging approaches. It has been found that these filters achieve noise reduction without loss of structural detail information, as indicated by their higher structure similarity indices, peak signal to noise ratios and the new variogram based quality measures.

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Authors and Affiliations

  1. Faculty of Computer Science and Engineering, Ghulam Ishaq Khan (GIK) Institute of Engineering Science and Technology, Topi-23460, Swabi, Pakistan

    Anwar M. Mirza, Asmatullah Chaudhry & Badre Munir

Authors
  1. Anwar M. Mirza
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  2. Asmatullah Chaudhry
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  3. Badre Munir
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Corresponding author

Correspondence to Anwar M. Mirza.

Additional information

This work has been sponsored by the Higher Education Commission, Government of Pakistan under the Scholarship Grant No. 17-6(176)Sch/2001.

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Mirza, A.M., Chaudhry, A. & Munir, B. Spatially Adaptive Image Restoration Using Fuzzy Punctual Kriging. J Comput Sci Technol 22, 580–589 (2007). https://doi.org/10.1007/s11390-007-9061-3

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  • DOI: https://doi.org/10.1007/s11390-007-9061-3

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