par Schretter, Colas 
;Loris, Ignace ;Dooms, Ann;Schelkens, P.
Editeur scientifique Jacques, L.;Boursier, Yannick;De Mol, Christine;Anthoine, Sandrine;Frossard, Pascal;De Vleeschouwer, Christophe;Sudhakar, Prasad;Pizurica, Aleksandra;Vandergheynst, Pierre
Référence international Traveling Workshop on Interactions between Sparse models and Technology(27-29/8/2014: Namur, Belgique), Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14), page (57-58)
Publication Publié, 2014-10-09
;Loris, Ignace ;Dooms, Ann;Schelkens, P.Editeur scientifique Jacques, L.;Boursier, Yannick;De Mol, Christine
;Anthoine, Sandrine;Frossard, Pascal;De Vleeschouwer, Christophe;Sudhakar, Prasad;Pizurica, Aleksandra;Vandergheynst, PierreRéférence international Traveling Workshop on Interactions between Sparse models and Technology(27-29/8/2014: Namur, Belgique), Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14), page (57-58)
Publication Publié, 2014-10-09
Publication dans des actes
| Résumé : | Pseudo-random numbers are often used for generating incoherent uniformly distributed sample distributions. However randomness is a sufficient – not necessary – condition to ensure incoherence. If one wants to reconstruct an image from few samples, choosing a globally optimized set of evenly distributed points could capture the visual content more efficiently. This work compares classical random sampling with a simple construction based on properties of the fractional Golden ratio sequence and the Hilbert space filling curve. Images are then reconstructed using a total variation prior. Results show improvements in terms of peak signal to noise ratio over pseudo-random sampling. |
