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Proceedings Paper

Sampling rates and image reconstruction from scattered fields
Author(s): Umer Shahid; Michael A. Fiddy; Markus E. Testorf
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Paper Abstract

Cepstral filtering is reviewed as a suitable and efficient method to solve the inverse scattering problem in the case of strongly scattering permittivity distributions. The number and distribution of measured scattered field data required is discussed, as is the effective number of degrees of freedom available to describe the scattering structure. The latter is identified as a key parameter determining the performance of the cepstral method. This is of particular importance for strong scattering and nonlinear image processing methods since many data sets are compiled based on the sampling requirements of weakly scattering objects. We find that the domain of the object support and the maximum permittivity contrast are important prior information for determining the minimum number of data samples necessary while maximizing use of the available degrees of freedom; examples are presented.

Paper Details

Date Published: 27 August 2010
PDF: 10 pages
Proc. SPIE 7800, Image Reconstruction from Incomplete Data VI, 780005 (27 August 2010); doi: 10.1117/12.861454
Show Author Affiliations
Umer Shahid, The Univ. of North Carolina at Charlotte (United States)
Michael A. Fiddy, The Univ. of North Carolina at Charlotte (United States)
Markus E. Testorf, Dartmouth College (United States)


Published in SPIE Proceedings Vol. 7800:
Image Reconstruction from Incomplete Data VI
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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