Title :
Image restoration by ordinary kriging with convexity
Author_Institution :
Sch. of Comput., Univ. of Canberra, ACT, Australia
Abstract :
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
Keywords :
Gaussian noise; filtering theory; image restoration; statistical analysis; white noise; Gaussian white noise; convexity; degraded images; image restoration; kriging filter; negative kriging weights; nonconvex estimation technique; Adaptive filters; Digital filters; Digital images; Filtering; Image restoration; Noise reduction; Nonlinear filters; Pixel; White noise; Wiener filter;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.903552