An ordinary kriging based approach for restoring degraded images is presented in this paper. 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. Experiments on an image degraded with different levels of Gaussian white noise are given to illustrate the effectiveness of the proposed approach. As a result, noisy images restored by ordinary kriging filter are more favorable than those restored by the adaptive Wiener filter.