Title
Spherical Designs and Nonconvex Minimization for Recovery of Sparse Signals on the Sphere.
Abstract
This paper considers the use of spherical designs and nonconvex minimization for recovery of sparse signals on the unit sphere S-2. The available information consists of low order, potentially noisy, Fourier coefficients for S-2. As Fourier coefficients are integrals of the product of a function and spherical harmonics, a good cubature rule is essential for the recovery. A spherical t-design is a set of points on S-2, which are nodes of an equal weight cubature rule integrating exactly all spherical polynomials of degree <= t. We will show that a spherical t-design provides a sharp error bound for the approximation signals. Moreover, the resulting coefficient matrix has orthonormal rows. In general the l(1) minimization model for recovery of sparse signals on S-2 using spherical harmonics has infinitely many minimizers, which means that most existing sufficient conditions for sparse recovery do not hold. To induce the sparsity, we replace the l(1)-norm by the l(q)-norm (0 < q < 1) in the basis pursuit denoise model. Recovery properties and optimality conditions are discussed. Moreover, we show that the penalty method with a starting point obtained from the reweighted l(1) method is promising to solve the l(q) basis pursuit denoise model. Numerical performance on nodes using spherical t-designs and t(epsilon)-designs (extremal fundamental systems) are compared with tensor product nodes. We also compare the basis pursuit denoise problem with q = 1 and 0 < q < 1.
Year
DOI
Venue
2018
10.1137/17M1147378
SIAM JOURNAL ON IMAGING SCIENCES
Keywords
Field
DocType
sparse recovery,quasi-norm,spherical design,nonconvex minimization,spherical cubature,reweighted l(1)
Coefficient matrix,Polynomial,Mathematical analysis,Spherical harmonics,Orthonormal basis,Minification,Fourier series,Spherical design,Mathematics,Unit sphere
Journal
Volume
Issue
ISSN
11
2
1936-4954
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Xiaojun Chen11298107.51
Robert S. Womersley225874.51