Compressive Sensing for Polyharmonic Subdivision Wavelets With   Applications to Image Analysis
  We apply successfully the Compressive Sensing approach for Image Analysis using the new family of Polyharmonic Subdivision wavelets. We show that this approach provides a very efficient recovery of the images based on fewer samples than the traditional Shannon-Nyquist paradigm. We provide the results of experiments with PHSD wavelets and Daubechies wavelets, for the Lena image and astronomical images. 
Ognyan Kounchev, Damyan Kalaglarsky
math.NA