Regularized total least squares reconstruction for optical tomographic imaging using conjugate gradient method

Wenwu Zhu, Yao Wang, Nikolas P. Galatsanos, Jun Zhang

Research output: Contribution to conferencePaper

Abstract

In this paper, a regularized total least square (RTLS) approach to solve a linear perturbation equation encountered in optical tomography is developed based on the Rayleigh quotient formulation. To compute efficiently the solution, the Rayleigh quotient form of the RTLS filter (RQF-RTLS) is used and a conjugate gradient algorithm is implemented. Simulation results show that the RQF-RTLS method obtains more stable and accurate solutions than the regularized least squares (RLS) approach which does not account for the errors in the operator.

Original languageEnglish (US)
Pages192-195
Number of pages4
StatePublished - 1997
EventProceedings of the 1997 International Conference on Image Processing. Part 2 (of 3) - Santa Barbara, CA, USA
Duration: Oct 26 1997Oct 29 1997

Other

OtherProceedings of the 1997 International Conference on Image Processing. Part 2 (of 3)
CitySanta Barbara, CA, USA
Period10/26/9710/29/97

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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  • Cite this

    Zhu, W., Wang, Y., Galatsanos, N. P., & Zhang, J. (1997). Regularized total least squares reconstruction for optical tomographic imaging using conjugate gradient method. 192-195. Paper presented at Proceedings of the 1997 International Conference on Image Processing. Part 2 (of 3), Santa Barbara, CA, USA, .