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We develop a sampling scheme on the sphere that permits accurate computation of the spherical harmonic transform and its inverse for signals band-limited at $L$ using only $L^2$ samples. We obtain the optimal number of samples given by the…

Information Theory · Computer Science 2014-07-25 Zubair Khalid , Rodney A. Kennedy , Jason D. McEwen

We propose a sampling scheme on the sphere and develop a corresponding spherical harmonic transform (SHT) for the accurate reconstruction of the diffusion signal in diffusion magnetic resonance imaging (dMRI). By exploiting the antipodal…

Medical Physics · Physics 2015-02-26 Alice P. Bates , Zubair Khalid , Rodney A. Kennedy

For the representation of spin-$s$ band-limited functions on the sphere, we propose a sampling scheme with optimal number of samples equal to the number of degrees of freedom of the function in harmonic space. In comparison to the existing…

Instrumentation and Methods for Astrophysics · Physics 2018-09-06 Usama Elahi , Zubair Khalid , Rodney A. Kennedy , Jason D. McEwen

We present the generalized iterative residual fitting (IRF) for the computation of the spherical harmonic transform (SHT) of band-limited signals on the sphere. The proposed method is based on the partitioning of the subspace of…

Information Theory · Computer Science 2017-09-11 Usama Elahi , Zubair Khalid , Rodney A. Kennedy , Jason D. McEwen

This paper proposes a multi-shell sampling scheme and corresponding transforms for the accurate reconstruction of the diffusion signal in diffusion MRI by expansion in the spherical polar Fourier (SPF) basis. The sampling scheme uses an…

Computer Vision and Pattern Recognition · Computer Science 2017-05-15 Alice P. Bates , Zubair Khalid , Jason D. McEwen , Rodney A. Kennedy

We propose a transform for signals defined on the sphere that reveals their localized directional content in the spatio-spectral domain when used in conjunction with an asymmetric window function. We call this transform the directional…

Information Theory · Computer Science 2013-04-23 Z. Khalid , R. A. Kennedy , S. Durrani , P. Sadeghi , Y. Wiaux , J. D. McEwen

We present spatial-Slepian transform~(SST) for the representation of signals on the sphere to support localized signal analysis. We use well-optimally concentrated Slepian functions, obtained by solving the Slepian spatial-spectral…

Signal Processing · Electrical Eng. & Systems 2021-09-01 Adeem Aslam , Zubair Khalid

A new lower bound on the average reconstruction error variance of multidimensional sampling and reconstruction is presented. It applies to sampling on arbitrary lattices in arbitrary dimensions, assuming a stochastic process with constant,…

Information Theory · Computer Science 2018-06-19 Erik Agrell , Balázs Csébfalvi

In this paper, we attempt to study the conditioning of the Spherical Harmonic Matrix (SHM), which is widely used in the discrete, limited order orthogonal representation of sound fields. SHM's has been widely used in the audio applications…

Audio and Speech Processing · Electrical Eng. & Systems 2018-03-07 C Sandeep Reddy , Rajesh M Hegde

This paper proposes a new approach to construct high quality space-filling sample designs. First, we propose a novel technique to quantify the space-filling property and optimally trade-off uniformity and randomness in sample designs in…

We study the impact of sampling theorems on the fidelity of sparse image reconstruction on the sphere. We discuss how a reduction in the number of samples required to represent all information content of a band-limited signal acts to…

Information Theory · Computer Science 2013-04-17 J. D. McEwen , G. Puy , J. -Ph. Thiran , P. Vandergheynst , D. Van De Ville , Y. Wiaux

We propose a multi-shell sampling grid and develop corresponding transforms for the accurate reconstruction of the diffusion signal in diffusion MRI by expansion in the spherical polar Fourier (SPF) basis. The transform is exact in the…

Discrete Mathematics · Computer Science 2017-02-24 Alice P. Bates , Zubair Khalid , Rodney A. Kennedy , Jason D. McEwen

In many applications data are measured or defined on a spherical manifold; spherical harmonic transforms are then required to access the frequency content of the data. We derive algorithms to perform forward and inverse spin spherical…

Astrophysics · Physics 2011-10-28 J. D. McEwen

We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our algorithm is a generalization of the annihilating filter method, a tool…

Information Theory · Computer Science 2016-01-20 Ivan Dokmanic , Yue M. Lu

The creation of optimal samplers can be a challenging task, especially in the presence of constraints on the support of parameters. One way of mitigating the severity of this challenge is to work with transformed variables, where the…

Methodology · Statistics 2021-10-22 Sharang Chaudhry , Daniel Lautzenheiser , Kaushik Ghosh

In practice, the finite number of samples of the spherical radiation pattern or antenna gain are taken on the sphere for both the reconstruction of the antenna radiation pattern and the computation of mobile handset performance measures…

Signal Processing · Electrical Eng. & Systems 2018-12-03 Umair Ahmed , Zubair Khalid

In this paper, we report on very efficient algorithms for the spherical harmonic transform (SHT). Explicitly vectorized variations of the algorithm based on the Gauss-Legendre quadrature are discussed and implemented in the SHTns library…

Computational Physics · Physics 2015-01-08 Nathanaël Schaeffer

In 3D single particle imaging with X-ray free-electron lasers, particle orientation is not recorded during measurement but is instead recovered as a necessary step in the reconstruction of a 3D image from the diffraction data. Here we use…

Data Analysis, Statistics and Probability · Physics 2016-05-25 Julien Flamant , Nicolas Le Bihan , Andrew V. Martin , Jonathan H. Manton

High-dimensional simulation optimization is notoriously challenging. We propose a new sampling algorithm that converges to a global optimal solution and suffers minimally from the curse of dimensionality. The algorithm consists of two…

Machine Learning · Statistics 2021-07-21 Liang Ding , Rui Tuo , Xiaowei Zhang

In the last decade diffusion MRI has become a powerful tool to non-invasively study white-matter integrity in the brain. Recently many research groups have focused their attention on multi-shell spherical acquisitions with the aim of…

Quantitative Methods · Quantitative Biology 2011-06-02 A. Daducci , J. D. McEwen , D. Van De Ville , J. -Ph. Thiran , Y. Wiaux
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