Use of Nonquadratic Regularization in Fourier Imaging

In many Fourier imaging applications, the presence of unaccounted for amplitude or phase errors in the Fourier domain data can lead to a degraded system impulse response and high sidelobes in the image domain. Historically, many methods for data-driven correction of these effects have been proposed,...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2009-01, Vol.45 (1), p.250-265
Main Author: Rigling, B.D.
Format: Article
Language:English
Subjects:
Algorithms
Apertures
Degradation
Discrete Fourier transforms
Fourier analysis
Fourier transforms
Frequency
History
Imaging
Impulse response
Layout
Mathematical models
Noise robustness
Optical imaging
Regularization
Sensor systems
Sidelobes
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Summary:In many Fourier imaging applications, the presence of unaccounted for amplitude or phase errors in the Fourier domain data can lead to a degraded system impulse response and high sidelobes in the image domain. Historically, many methods for data-driven correction of these effects have been proposed, and numerical optimization of nonquadratic, p -norm image quality metrics has recently emerged as a robust solution. This paper presents a tutorial examination of the sources of image sidelobes in Fourier imaging applications, and studies the effectiveness of p -norm regularization algorithms under various experimental conditions. Several observations are made, including comments on robustness to noise and methods for tapered window design and energy-constrained sparse aperture imaging. Image examples are presented as experimental validation.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2009.4805277