Limited-angle reconstruction from noisy data using clustering of the solution space

Meir Feder*, Jules S. Jaffe

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

The authors propose a stabilized method for limited angle reconstruction. The algorithm provides a framework that makes it possible to incorporate prior information and to account for the noise; this framework is the reason for the method's stability. The method entails the following steps: 1) a space of reconstruction solutions is generated, either analytically or by Monte Carlo simulation; 2) representatives of the solutions are found by clustering the solution space; and 3) these representatives are scored, using the a priori information, to define the final solution. Simulation results are presented for a simple 1-D deconvolution problem.

Original languageEnglish
Pages (from-to)1516-1519
Number of pages4
JournalProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Volume3
StatePublished - 1989
Externally publishedYes
Event1989 International Conference on Acoustics, Speech, and Signal Processing - Glasgow, Scotland
Duration: 23 May 198926 May 1989

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