DocumentCode
1742237
Title
Image restoration by ordinary kriging with convexity
Author
Pham, Tuan D.
Author_Institution
Sch. of Comput., Univ. of Canberra, ACT, Australia
Volume
3
fYear
2000
fDate
2000
Firstpage
330
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location
Barcelona
ISSN
1051-4651
Print_ISBN
0-7695-0750-6
Type
conf
DOI
10.1109/ICPR.2000.903552
Filename
903552
Link To Document