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Noise reduction algorithms using fibonacci fourier transforms
Agaian S.S.; Chen M.-C.; Chen C.L.P.
2008-12-01
Source PublicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Pages1048-1052
AbstractThis paper presents the new Fibonacci Fourier-like transforms. The proposed transforms render the relationship between Fibonacci numbers and the conventional Discrete Fourier Transform. The fast Fibonacci Fourier transforms are also introduced with the use of the Kronecker product properties. The proposed transforms are applied to the problem of noise reduction with two new algorithms, sliding double window filtering and fusion sliding window filtering. The primary concept of sliding double window filtering is to process the noisy signals with nonoverlapped windows, while the primary concept of fusion sliding window filtering is to process the noisy signals with various weighted filtering methods and overlapped signal values. The results and analysis show the noise reduction of the given noisy gray level images. The proposed methods are compared with the well-known Wiener filtering using images that contain Gaussian noise with the range of variance between 0 and 0.3. The analysis shows by visual inspection that the noisy parts are smoothened while retaining natural edges. © 2008 IEEE.
KeywordFast fibonacci fourier transforms Fibonacci fourier transforms Noise reduction Sliding window filters
DOI10.1109/ICSMC.2008.4811420
URLView the original
Language英語
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Document TypeConference paper
CollectionUniversity of Macau
AffiliationUniversity of Texas at San Antonio
Recommended Citation
GB/T 7714
Agaian S.S.,Chen M.-C.,Chen C.L.P.. Noise reduction algorithms using fibonacci fourier transforms[C],2008:1048-1052.
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