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Abstract
Pseudorandom 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 pseudorandom sampling.
Original language  English 

Title of host publication  iTWIST'14, international  Traveling Workshop on Interactions between Sparse models and Technology 
Editors  Laurent Jacques 
Pages  5758 
Publication status  Published  2014 
Event  iTWIST'14 international Traveling Workshop on Interactions between Sparse models and Technology  Namur, Belgium Duration: 27 Aug 2014 → 29 Aug 2014 
Conference
Conference  iTWIST'14 international Traveling Workshop on Interactions between Sparse models and Technology 

Country  Belgium 
City  Namur 
Period  27/08/14 → 29/08/14 
Bibliographical note
Laurent JacquesKeywords
 Compressed sensing
 Total variation
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SRP11: Strategic Research Programme: Processing of large scale multidimensional, multispectral, multisensorial and distributed data (M³D²)
Schelkens, P., Deligiannis, N., Jansen, B., Kuijk, M., Munteanu, A., Sahli, H., Steenhaut, K., Stiens, J., Schelkens, P., Cornelis, J. P., Kuijk, M., Munteanu, A., Sahli, H., Stiens, J. & Vounckx, R.
1/11/12 → 31/10/22
Project: Fundamental

EU465: INTERFERE: Sparse Signal Coding for Interferencebased Imaging Modalities
1/06/14 → 31/05/19
Project: Fundamental