DocumentCode :
86733
Title :
Discrete Spherical Harmonic Oscillator Transforms on the Cartesian Grids Using Transformation Coefficients
Author :
Soo-Chang Pei ; Chun-Lin Liu
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Volume :
61
Issue :
5
fYear :
2013
fDate :
1-Mar-13
Firstpage :
1149
Lastpage :
1164
Abstract :
The analog harmonic oscillators are well-studied in quantum physics, including their energy states, wavefunctions, orthogonal properties, and eigenfunctions of the Fourier transform. In addition, the continuous solutions in different dimension and coordinate systems are known. Some discrete equivalents of the 1D wavefunctions were also studied. However, in the 3D spherical coordinate system, the discrete equivalents of the 3D wavefunctions are not established. In this paper, we focus on the spherical harmonic oscillator wavefunctions (SHOWs) the spherical harmonic oscillator transforms (SHOTs), and their discrete implementation. The SHOWs can be synthesized by linear combinations of the Hermite Gaussian functions with proper transformation coefficients. We find that computing the coefficients can be speeded up using the fast Fourier transforms or some recursive relations. These coefficients relate the Hermite transforms with the SHOTs. Some applications of the discrete SHOWs and the discrete SHOTs are introduced. First, the SHOWs are exactly the eigenfunctions of the 3D DFT. Also, the SHOTs can be used to derive the spherical harmonic oscillator descriptor (SHOD), which is a rotational invariant descriptor. We find that the SHOD is not only compatible with the existing rotational descriptors for the spherically sampled data but also outperforms the existing rotational descriptors for 3D Cartesian sampled, bandlimited input data. Besides, the SHOTs can be used to decompose 3D signals into spherical components. Hence, 3D signal reconstruction is done using partially chosen spherical component, and 3D data compression for MRI data is demonstrated using SHOTs for medical applications.
Keywords :
Gaussian processes; biomedical MRI; data compression; eigenvalues and eigenfunctions; fast Fourier transforms; harmonic oscillators; image reconstruction; medical image processing; 1D wavefunctions; 3D DFT eigenfunctions; 3D cartesian; 3D data compression; 3D signal reconstruction; 3D spherical coordinate system; 3D wavefunctions; Fourier transform; Hermite Gaussian functions; Hermite transforms; MRI data; SHOD; SHOT; SHOW; analog harmonic oscillators; cartesian grids; discrete spherical harmonic oscillator transforms; eigenfunctions; energy states; medical applications; orthogonal properties; quantum physics; recursive relations; rotational descriptors; spherical harmonic oscillator descriptor; spherical harmonic oscillator wavefunctions; transformation coefficients; Discrete Fourier transforms; Eigenvalues and eigenfunctions; Harmonic analysis; Oscillators; Vectors; Fast Fourier transforms; Fourier transforms; harmonic analysis; multidimensional signal processing; quantum harmonic oscillators; rotational invariant descriptors;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2012.2232658
Filename :
6375857
Link To Document :
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