Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/82375
Title: Sampling Signals With a Finite Rate of Innovation on the Sphere
Authors: Deslauriers-Gauthier, Samuel
Marziliano, Pina
Keywords: Annihilating filter
Finite rate of innovation
Spherical convolution
Spherical harmonic
Sampling theorem
Issue Date: 2013
Source: Deslauriers-Gauthier, S.,& Marziliano, P. (2013). Sampling Signals With a Finite Rate of Innovation on the Sphere. IEEE Transactions on Signal Processing, 61(18), 4552-4561.
Series/Report no.: IEEE Transactions on Signal Processing
Abstract: The state of the art in sampling theory now contains several theorems for signals that are non-bandlimited. For signals on the sphere however, most theorems still require the assumptions of bandlimitedness. In this work we show that a particular class of non-bandlimited signals, which have a finite rate of innovation, can be exactly recovered using a finite number of samples. We consider a sampling scheme where K weighted Diracs are convolved with a kernel on the rotation group. We prove that if the sampling kernel has a bandlimit L=2k then (2k - 1) (4k - 1) + 1 equiangular samples are sufficient for exact reconstruction. If the samples are uniformly distributed on the sphere, we argue that the signal can be accurately reconstructed using 4K2 samples and validate our claim through numerical simulations. To further reduce the number of samples required, we design an optimal sampling kernel that achieves accurate reconstruction of the signal using only 3K samples, the number of parameters of the weighted Diracs. In addition to weighted Diracs, we show that our results can be extended to sample Diracs integrated along the azimuth. Finally, we consider kernels with antipodal symmetry which are common in applications such as diffusion magnetic resonance imaging.
URI: https://hdl.handle.net/10356/82375
http://hdl.handle.net/10220/39989
DOI: 10.1109/TSP.2013.2272289
Rights: © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TSP.2013.2272289].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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