Compressed Sensing Overview

Information

• Publication Type: Student Project
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: 2008
• First Supervisor: Erald Vucini

Abstract

Compressed sensing (or Compressive sampling) tries to exploit the sparsity of signals to either improve the quality of reconstructions, or reduce the required number of samples. The samples are usually taken by multiplication with some matrix with independent — normally distributed — random values, or by selecting values from the Fourier transform of a signal. Important is that the signal should not be sparse in the transformed domain. How many samples need to be taken depend on the characteristics of the matrix and the signal. Several introductory texts, as well as a lot of reference material, can be found on http://www.dsp.ece.rice.edu/cs/.

Additional Files and Images

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BibTeX

@studentproject{Gronde_2008,
  title =      "Compressed Sensing Overview",
  author =     "Jasper  van de Gronde",
  year =       "2008",
  abstract =   "Compressed sensing (or Compressive sampling) tries to
               exploit the sparsity of signals to either improve the
               quality of reconstructions, or reduce the required number of
               samples. The samples are usually taken by multiplication
               with some matrix with independent — normally distributed
               — random values, or by selecting values from the Fourier
               transform of a signal. Important is that the signal should
               not be sparse in the transformed domain. How many samples
               need to be taken depend on the characteristics of the matrix
               and the signal. Several introductory texts, as well as a lot
               of reference material, can be found on
               http://www.dsp.ece.rice.edu/cs/.",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2008/Gronde_2008/",
}