DocumentCode
1855660
Title
A fuzzy-Bayesian approach to image expansion
Author
Sakalli, M. ; Yan, Hong ; Fu, Alan M N
Author_Institution
Dept. of Electr. & Inf. Eng., Sydney Univ., NSW, Australia
Volume
4
fYear
1999
fDate
1999
Firstpage
2685
Abstract
This paper presents a fuzzy edge preserving interpolation method for digital images to reduce the effect of jaggedness and blurring artifacts along the high contrast edges. A high subjective performance is achieved by combining two techniques, a region segmentation method and a fuzzy inference method based on the Bayesian structure
Keywords
Bayes methods; computer vision; fuzzy logic; image restoration; image segmentation; inference mechanisms; interpolation; inverse problems; Bayesian structure; Gibbs energy function; digital images; edge preserving; fuzzy inference; image expansion; interpolation; inverse problem; region segmentation; Australia; Bayesian methods; Cameras; Frequency; Image reconstruction; Image resolution; Image segmentation; Low pass filters; Samarium; Spline;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-5529-6
Type
conf
DOI
10.1109/IJCNN.1999.833502
Filename
833502
Link To Document