DocumentCode
1436147
Title
2-D and 1-D multipaired transforms: frequency-time type wavelets
Author
Grigoryan, Artyom M.
Author_Institution
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
Volume
49
Issue
2
fYear
2001
fDate
2/1/2001 12:00:00 AM
Firstpage
344
Lastpage
353
Abstract
A concept of multipaired unitary transforms is introduced. These kinds of transforms reveal the mathematical structure of Fourier transforms and can be considered intermediate unitary transforms when transferring processed data from the original real space of signals to the complex or frequency space of their images. Considering paired transforms, we analyze simultaneously the splitting of the multidimensional Fourier transform as well as the presentation of the processed multidimensional signal in the form of the short one-dimensional (1-D) “signals”, that determine such splitting. The main properties of the orthogonal system of paired functions are described, and the matrix decompositions of the Fourier and Hadamard transforms via the paired transforms are given. The multiplicative complexity of the two-dimensional (2-D) 2r×2r-point discrete Fourier transform by the paired transforms is 4r/2(r-7/3)+8/3-12 (r>3), which shows the maximum splitting of the 5-D Fourier transform into the number of the short 1-D Fourier transforms. The 2-D paired transforms are not separable and represent themselves as frequency-time type wavelets for which two parameters are united: frequency and time. The decomposition of the signal is performed in a way that is different from the traditional Haar system of functions
Keywords
discrete Fourier transforms; signal processing; time-frequency analysis; wavelet transforms; 1D multipaired transforms; 1D signal; 2D DFT; 2D discrete Fourier transform; 2D multipaired transforms; 2D paired transforms; 5D Fourier transform; Hadamard transforms; complex image space; frequency image space; frequency-time type wavelets; image processing; intermediate unitary transforms; mathematical structure; matrix decompositions; multidimensional Fourier transform splitting; multidimensional signal; multipaired unitary transforms; multiplicative complexity; orthogonal system; processed data; real signal space; short 1D Fourier transforms; signal processing; Discrete Fourier transforms; Discrete wavelet transforms; Fourier transforms; Frequency; Matrix decomposition; Multidimensional signal processing; Signal analysis; Signal processing; Two dimensional displays; Wavelet transforms;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.902116
Filename
902116
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