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Compressive Sensing for Polyharmonic Subdivision Wavelets With Applications to Image Analysis

Numerical Analysis 2012-04-19 v1

Abstract

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.

Keywords

Cite

@article{arxiv.1204.3996,
  title  = {Compressive Sensing for Polyharmonic Subdivision Wavelets With Applications to Image Analysis},
  author = {Ognyan Kounchev and Damyan Kalaglarsky},
  journal= {arXiv preprint arXiv:1204.3996},
  year   = {2012}
}

Comments

11 pages, 10 figures

R2 v1 2026-06-21T20:51:14.332Z