An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint - Archive ouverte HAL
Communication Dans Un Congrès Année : 2020

An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint

Résumé

Theoretical results show that sparse off-the-grid spikes can be estimated from (possibly compressive) Fourier measurements under a minimum separation assumption. We propose a practical algorithm to minimize the corresponding non-convex functional based on a projected gradient descent coupled with an initialization procedure. We give qualitative insights on the theoretical foundations of the algorithm and provide experiments showing its potential for imaging problems.
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Dates et versions

hal-03037264 , version 1 (03-12-2020)

Identifiants

  • HAL Id : hal-03037264 , version 1

Citer

Yann Traonmilin, Jean-François Aujol, Arthur Leclaire. An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint. in Proceedings of iTWIST'20, Paper-ID: 7, Nantes, France, December, 2-4, 2020, Dec 2020, Nantes, France. ⟨hal-03037264⟩

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