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Proceedings Paper

Positivity and support: a comparison
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Paper Abstract

Positivity and support have long been used to improve image quality beyond that achievable from the measured data alone. In this paper we analyze how positivity functions to reduce noise levels in measured Fourier data and the corresponding images. We show that positivity can be viewed as a signal- dependent support constraint, and thus it functions by enforcing Fourier-domain correlations. Using computer simulated data, we show the effects that positivity has upon measured Fourier data and upon images. We compare these results to equivalent result obtained using support as constraint. We show that support is a more powerful constraint than positivity in several ways: (1) more super- resolution is possible, (2) more Fourier domain noise reduction can occur, and (3) more image-domain noise reduction can occur.

Paper Details

Date Published: 22 December 1997
PDF: 10 pages
Proc. SPIE 3217, Image Processing, Signal Processing, and Synthetic Aperture Radar for Remote Sensing, (22 December 1997); doi: 10.1117/12.295603
Show Author Affiliations
Charles L. Matson, Air Force Phillips Lab. (United States)
David W. Tyler, Schafer Associates (United States)


Published in SPIE Proceedings Vol. 3217:
Image Processing, Signal Processing, and Synthetic Aperture Radar for Remote Sensing
Jacky Desachy; Shahram Tajbakhsh, Editor(s)

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