22 December 1997 Positivity and support: a comparison
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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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Charles L. Matson, David W. Tyler, "Positivity and support: a comparison", Proc. SPIE 3217, Image Processing, Signal Processing, and Synthetic Aperture Radar for Remote Sensing, (22 December 1997); doi: 10.1117/12.295603; https://doi.org/10.1117/12.295603
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Computer simulations

Denoising

Image quality

Image resolution

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