Implications for compressed sensing of a new sampling theorem on the sphere

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.


Published in:
Proceedings of the 4th Workshop on Signal Processing with Adaptive Sparse Structured Representations, 45
Presented at:
4th Workshop on Signal Processing with Adaptive Sparse Structured Representations, Edinburgh, Scotland, 27-30 June, 2011
Year:
2011
Keywords:
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 Record created 2011-04-20, last modified 2018-03-18

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