Multiresolution regularized least squares image reconstruction based on wavelet in optical tomography

Wenwu Zhu, Yao Wang, Yining Deng, Yuqi Yao, Randall L. Barbour

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present a wavelet based multigrid approach to solve the perturbation equation encountered in optical tomography. With this scheme, the unknown image, the data, as well as weight matrix are all represented by wavelet expansions, and thus yielding a multiresolution representation of the original perturbation equation in the wavelet domain. This transformed equation is then solved using multigrid scheme, by which an increasing portion of wavelet coefficients of the unknown image are solved in successive approximations. One can also quickly identify regions of interest from a coarse level reconstruction and restrict the reconstruction in the following fine resolutions to those regions. At each resolution level, a regularized least squares solution is obtained using a conjugate gradient descent method. Compared to a previously reported one grid algorithm, the multigrid method requires substantially shorter computation time under the same reconstruction quality criterion.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsRandall L. Barbour, Mark J. Carvlin, Michael A. Fiddy
Pages186-196
Number of pages11
StatePublished - 1995
EventExperimental and Numerical Methods for Solving Ill-Posed Inverse Problems: Medical and Nonmedical Applications - San Diego, CA, USA
Duration: Jul 10 1995Jul 11 1995

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume2570
ISSN (Print)0277-786X

Other

OtherExperimental and Numerical Methods for Solving Ill-Posed Inverse Problems: Medical and Nonmedical Applications
CitySan Diego, CA, USA
Period7/10/957/11/95

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Zhu, W., Wang, Y., Deng, Y., Yao, Y., & Barbour, R. L. (1995). Multiresolution regularized least squares image reconstruction based on wavelet in optical tomography. In R. L. Barbour, M. J. Carvlin, & M. A. Fiddy (Eds.), Proceedings of SPIE - The International Society for Optical Engineering (pp. 186-196). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 2570).