2011/10/28 by Jason D. McEwen, Gilles Puy, McEwen, J. D. +9
Computer Science · Earth and Planetary Sciences · Engineering · #FOS: Computer and information sciences #FOS: Physical sciences #Image and Signal Denoising Methods #Information Theory (cs.IT) #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Seismic Imaging and Inversion Techniques #Sparse and Compressive Sensing Techniques
paper · pdf · doi:10.48550/arxiv.1110.6296
openalex publication_date 2011/10/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A sampling theorem on the sphere has been developed recently, requiring half as many samples as alternative equiangular sampling theorems on the sphere. A reduction by a factor of two in the number of samples required to represent a band-limited signal on the sphere exactly has important implications for compressed sensing, both in terms of the dimensionality and sparsity of signals. We illustrate the impact of this property with an inpainting problem on the sphere, where we show the superior reconstruction performance when adopting the new sampling theorem compared to the alternative.