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Proceedings Paper

Spatially adaptive image restoration for autoradiography
Author(s): John A. Goyette; Moon Gi Kang; Aggelos K. Katsaggelos; Gregory D. Lapin
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Paper Abstract

In this paper, we present a model that is used to improve the resolution of autoradiographic images. The model involves a point spread function (PSF) due to the radiated pattern of emitted photons combined with a signal-dependent noise source due to the granularity of x-ray recording film. A theoretical expression for the PSF is presented, and experimental measurements are performed using 51Cr microspheres. An iterative regularized image restoration algorithm is developed using a weighting matrix to incorporate the signal- dependent nature of the noise. Since information about the original undegraded image is not completely available, we make use of a regualtization functional that is updated at each iteration to optimize the solution process. Our experimental results indicate that the resolution of autoradiographic images is improved by 43% using this algorithm.

Paper Details

Date Published: 18 August 1995
PDF: 12 pages
Proc. SPIE 2622, Optical Engineering Midwest '95, (18 August 1995); doi: 10.1117/12.216883
Show Author Affiliations
John A. Goyette, Northwestern Univ. (United States)
Moon Gi Kang, Univ. of Minnesota (United States)
Aggelos K. Katsaggelos, Northwestern Univ. (United States)
Gregory D. Lapin, Northwestern Univ. (United States)

Published in SPIE Proceedings Vol. 2622:
Optical Engineering Midwest '95
Rudolph P. Guzik, Editor(s)

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