Paper Info
Title
A new fuzzy-based wavelet shrinkage image denoising technique
Abstract
This paper focuses on fuzzy image denoising techniques. In particular, we investigate the usage of fuzzy set theory in the domain of image enhancement using wavelet thresholding. We propose a simple but efficient new fuzzy wavelet shrinkage method, which can be seen as a fuzzy variant of a recently published probabilistic shrinkage method [1] for reducing adaptive Gaussian noise from digital greyscale images. Experimental results show that the proposed method can efficiently and rapidly remove additive Gaussian noise from digital greyscale images. Numerical and visual observations show that the performance of the proposed method outperforms current fuzzy non-wavelet methods and is comparable with some recent but more complex wavelets methods. We also illustrate the main differences between this version and the probabilistic version and show the main improvements in comparison to it.
Year
DOI
Venue
2006
10.1007/11864349_2
ACIVS
Keywords
Field
DocType
new fuzzy-based wavelet shrinkage,complex wavelets method,fuzzy set theory,current fuzzy non-wavelet method,shrinkage method,efficient new fuzzy wavelet,digital greyscale image,fuzzy variant,probabilistic shrinkage method,fuzzy image,gaussian noise
Computer vision,Pattern recognition,Computer science,Fuzzy logic,Image processing,Digital image,Fuzzy set,Artificial intelligence,Image restoration,Gaussian noise,Fuzzy rule,Wavelet
Conference
Volume
ISSN
ISBN
4179
0302-9743
3-540-44630-3
Citations 
PageRank 
References 
19
0.87
24
Authors
5
Name
Order
Citations
PageRank
Stefan Schulte127717.53
Bruno Huysmans2272.12
Aleksandra Pizurica31238102.29
Etienne E. Kerre43909331.20
Wilfried Philips51476124.85