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Proceedings Paper

Variance reduction in Fourier spectra and their corresponding images via support constraints
Author(s): Charles L. Matson
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Paper Abstract

The use of support constraints for improving the quality of Fourier spectra, their associated images, and the relationship between the two domains is discussed in this paper. Theoretical relationships are derived which predict the noise reduction in both the image domain and the Fourier domain achieved by single and repeated application of support constraints for the case of wide sense stationary Fourier domain noise. It is shown that the application of support constraints can increase noise inside the support constraint if the application is not done correctly. An iterative algorithm is proposed which enforces support constraints in such a way that noise is never increased inside the support constraint and the algorithm achieves the minimum possible noise in a finite number of steps.

Paper Details

Date Published: 9 November 1993
PDF: 11 pages
Proc. SPIE 2029, Digital Image Recovery and Synthesis II, (9 November 1993); doi: 10.1117/12.162015
Show Author Affiliations
Charles L. Matson, Seattle Pacific Univ. (United States)


Published in SPIE Proceedings Vol. 2029:
Digital Image Recovery and Synthesis II
Paul S. Idell, Editor(s)

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