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Total Variation Reconstruction From Quasi-Random Samples Host Publication: iTWISTཊ international Traveling Workshop on Interactions between Sparse models and Technology Authors: C. Schretter, I. Loris, A. Dooms and P. Schelkens Publication Year: 2014
Abstract: 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. External Link.
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