Asymptotically Steerable Finite Fourier-Bessel Transforms and Closure under Convolution.

CoRR(2023)

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摘要
This paper develops a constructive numerical scheme for Fourier-Bessel approximations on disks compatible with convolutions supported on disks. We address accurate finite Fourier-Bessel transforms (FFBT) and inverse finite Fourier-Bessel transforms (iFFBT) of functions on disks using the discrete Fourier Transform (DFT) on Cartesian grids. Whereas the DFT and its fast implementation (FFT) are ubiquitous and are powerful for computing convolutions, they are not exactly steerable under rotations. In contrast, Fourier-Bessel expansions are steerable, but lose both this property and the preservation of band limits under convolution. This work captures the best features of both as the band limit is allowed to increase. The convergence/error analysis and asymptotic steerability of FFBT/ iFFBT are investigated. Conditions are established for the FFBT to converge to the Fourier-Bessel coefficient and for the iFFBT to uniformly approximate the Fourier-Bessel partial sums. The matrix form of the finite transforms is discussed. The implementation of the discrete method to compute numerical approximation of convolutions of compactly supported functions on disks is considered as well.
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关键词
convolution,fourier-bessel
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