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Toeplitz block matrices in compressed sensing and their applications in imaging

  • University of Wisconsin-Milwaukee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

55 Scopus citations

Abstract

Recent work in compressed sensing theory shows that sensing matrices whose entries are drawn independently from certain probability distributions guarantee exact recovery of a sparse signal from a small number of measurements with high probability. In most medical imaging systems, the encoding matrices cannot take that form. Instead, they are Toeplitz block matrix. Motivated by this fact, we consider Toeplitz block matrices as the sensing matrices. We show that the probability of perfect reconstruction from a smaller number of filter outputs is also high if the filter coefficients are independently and identically- distributed random variable. Their applications in medical imaging is discussed. Simulation results are also shown to validate the theorem.

Original languageEnglish
Title of host publication5th Int. Conference on Information Technology and Applications in Biomedicine, ITAB 2008 in conjunction with 2nd Int. Symposium and Summer School on Biomedical and Health Engineering, IS3BHE 2008
Pages47-50
Number of pages4
DOIs
StatePublished - 2008
Event5th International Conference on Information Technology and Applications in Biomedicine, ITAB 2008 in conjunction with 2nd International Symposium and Summer School on Biomedical and Health Engineering, IS3BHE 2008 - Shenzhen, China
Duration: May 30 2008May 31 2008

Publication series

Name5th Int. Conference on Information Technology and Applications in Biomedicine, ITAB 2008 in conjunction with 2nd Int. Symposium and Summer School on Biomedical and Health Engineering, IS3BHE 2008

Conference

Conference5th International Conference on Information Technology and Applications in Biomedicine, ITAB 2008 in conjunction with 2nd International Symposium and Summer School on Biomedical and Health Engineering, IS3BHE 2008
Country/TerritoryChina
CityShenzhen
Period05/30/0805/31/08

Keywords

  • Compressed sensing
  • Random point spread function
  • Toeplitz block matrix

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