Image restoration by fuzzy convex ordinary kriging

Author

Pham, Tuan D. ; Wagner, M.

Author_Institution

Sch. of Comput., Canberra Univ., ACT, Australia

Volume

1

fYear

2000

fDate

2000

Firstpage

113

Abstract

Ordinary kriging and fuzzy sets are combined to derive a spatial filter for restoring degraded images. As kriging is a nonconvex estimation technique and negative kriging weights applied to image data can give estimates outside the range of pixel values. Convexity is therefore required in this image analysis to ensure no negative weights. Fuzzy sets are used to enhance the smoothing process of an ordinary kriging filter. Experiments on an image degraded by Gaussian white noise are given to illustrate the effectiveness of the proposed approach in comparison with the adaptive Wiener filter

Keywords

Gaussian noise; filtering theory; fuzzy set theory; image restoration; parameter estimation; spatial filters; white noise; AWGN degraded image; adaptive Wiener filter; additive white Gaussian noise; fuzzy convex ordinary kriging; fuzzy sets; image analysis; image data; image restoration; intensity image smoothing; linear unbiased estimator; negative kriging weights; negative weights; nonconvex estimation; pixel values; spatial filter; Adaptive filters; Degradation; Filtering; Fuzzy sets; Gaussian noise; Image restoration; Nonlinear filters; Pixel; Smoothing methods; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2000. Proceedings. 2000 International Conference on

Conference_Location

Vancouver, BC

ISSN

1522-4880

Print_ISBN

0-7803-6297-7

Type

conf

DOI

10.1109/ICIP.2000.900905

Filename

900905