Image restoration by fuzzy convex ordinary kriging

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.