Abstract:
In this paper we show that the spatially localized spherical harmonic transform (SLSHT), which represents a signal on the 2-sphere in the spatio-spectral domain, can be e...Show MoreMetadata
Abstract:
In this paper we show that the spatially localized spherical harmonic transform (SLSHT), which represents a signal on the 2-sphere in the spatio-spectral domain, can be efficiently computed using new kernel-based formulations. In addition to the standard spatio-spectral domain, we show there are three other related transforms that provide alternative representations in the spatio-spatial, spectro-spatial and spectro-spectral domains. We provide inversion results that extend available results for the SLSHT. We show that for signals on the 2-sphere band-limited to degree L, the computational complexity using our class of kernel-based SLSHT transforms is O(L4) and outperforms the previous best known fast methods, which have complexity O(L5).
Published in: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Date of Conference: 04-09 May 2014
Date Added to IEEE Xplore: 14 July 2014
Electronic ISBN:978-1-4799-2893-4