Abstract #1190

Fast Variable Density Poisson-Disc Sample Generation with Directional Variation for Compressed Sensing

Nicholas Dwork¹, Corey A. Baron², Ethan M. I. Johnson³, Daniel O'Connor⁴, John M. Pauly⁵, and Peder E.Z. Larson¹

¹Radiology and Biomedical Imaging, UCSF, San Francisco, CA, United States, ²Robarts Research, Western University, Ontario, ON, Canada, ³Biomedical Engineering, Northwestern University, Evanston, IL, United States, ⁴Mathematics and Statistics, University of San Francisco, San Francisco, CA, United States, ⁵Electrical Engineering, Stanford University, Stanford, CA, United States

We present a fast method for generating a variable density poisson-disc sampling pattern. A minimum parameter value is used to create a background grid array for keeping track of those points that might affect any new candidate point; this reduces the number of conflicts that must be checked before acceptance of a new point, thus reducing the number of computations required. We demonstrate the algorithm's ability to generate variable density poisson-disc sampling patterns where the variations in density are a function of direction. We further show that these sampling patterns are appropriate for compressed sensing applications.

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