Sparse Image Reconstruction on the Sphere: Implications of a New Sampling Theorem

DOI10.1109/TIP.2013.2249079zbMath1373.94280arXiv1205.1013OpenAlexW2100952825WikidataQ45721201 ScholiaQ45721201MaRDI QIDQ5373405

Dimitri Van De Ville, Jason D. McEwen, Y. Wiaux, Gilles Puy, Jean-Philippe Thiran, Pierre Vandergheynst

Publication date: 27 October 2017

Published in: IEEE Transactions on Image Processing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1205.1013

Mathematics Subject Classification ID

Image analysis in multivariate analysis (62H35) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Sampling theory in information and communication theory (94A20)

Related Items (3)

Sketching with Spherical Designs for Noisy Data Fitting on Spheres ⋮ The stochastic properties of \(\ell^1\)-regularized spherical Gaussian fields ⋮ Exact recovery of Dirac ensembles from the projection onto spaces of spherical harmonics

This page was built for publication: Sparse Image Reconstruction on the Sphere: Implications of a New Sampling Theorem