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Proceedings Paper

Linear feature SNR enhancement in radon transform space
Author(s): John R. Meckley
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Paper Abstract

Many image features of interest are either linear in nature or are composed of piecewise linear segments. When the initial imaging process does not produce a signal-to-noise ratio sufficient for detection, a predetection filter is required to enhance the feature SNR. This filter must be invariant to feature position, orientation, and size in order to produce the highest processing gain with minimum distortion. The Fourier transform of the radon transform of linear features is shown to be invariant with respect to position and orientation, while varying slowly with respect to feature size. This permits optimum filtering for SNR enhancement. After filtering the radon transform, the image is reconstructed through a backprojection algorithm. Detection and segmentation of the linear features is significantly enhanced in the filtered image.

Paper Details

Date Published: 1 October 1991
PDF: 11 pages
Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); doi: 10.1117/12.48395
Show Author Affiliations
John R. Meckley, GE Advanced Technology Labs. (United States)


Published in SPIE Proceedings Vol. 1569:
Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision
Su-Shing Chen, Editor(s)

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