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Proceedings Paper

Improved radon based imaging using the shearlet transform
Author(s): Glenn R. Easley; Flavia Colonna; Demetrio Labate
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Paper Abstract

Many imaging modalities, such as Synthetic Aperture Radar (SAR), can be described mathematically as collecting data in a Radon transform domain. The process of inverting the Radon transform to form an image can be unstable when the data collected contain noise so that the inversion needs to be regularized in some way. In this work, we develop a method for inverting the Radon transform using a shearlet-based decomposition, which provides a regularization that is nearly optimal for a general class of images. We then show through a variety of examples that this technique performs better than similar competitive methods based on the use of the wavelet and the curvelet transforms.

Paper Details

Date Published: 19 March 2009
PDF: 10 pages
Proc. SPIE 7343, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VII, 734306 (19 March 2009); doi: 10.1117/12.820066
Show Author Affiliations
Glenn R. Easley, System Planning Corp. (United States)
Flavia Colonna, George Mason Univ. (United States)
Demetrio Labate, North Carolina State Univ. (United States)


Published in SPIE Proceedings Vol. 7343:
Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VII
Harold H. Szu; F. Jack Agee, Editor(s)

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