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Proceedings Paper

POPART - Performance Optimized Algebraic Reconstruction Technique
Author(s): K. M. Hanson
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Paper Abstract

A method for optimizing image-recovery algorithms is presented that is based on how well a specified visual task can be performed using the reconstructed images. Visual task performance is numerically assessed by a Monte Carlo simulation of the complete imaging process including the generation of scenes appropriate to the desired application, subsequent data taking, image recovery, and performance of the stated task based on the final image. This method is used to optimize the Algebraic Reconstruction Technique (ART), which reconstructs images from their projections, by varying the relaxation factor employed in the updating procedure. In some of the imaging situations studied, it is found that the optimization of constrained ART, in which a nonnegativity constraint is invoked, can vastly increase the detectability of objects. There is little improvement attained for unconstrained ART.

Paper Details

Date Published: 25 October 1988
PDF: 10 pages
Proc. SPIE 1001, Visual Communications and Image Processing '88: Third in a Series, (25 October 1988); doi: 10.1117/12.968969
Show Author Affiliations
K. M. Hanson, Los Alamos National Laboratory (United States)

Published in SPIE Proceedings Vol. 1001:
Visual Communications and Image Processing '88: Third in a Series
T. Russell Hsing, Editor(s)

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