Linear feature SNR enhancement in radon transform space

John R. Meckley

doi:10.1117/12.48395

1 October 1991 Linear feature SNR enhancement in radon transform space

John R. Meckley

Proceedings Volume 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision; (1991) https://doi.org/10.1117/12.48395
Event: San Diego, '91, 1991, San Diego, CA, United States

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.

Citation Download Citation

John R. Meckley "Linear feature SNR enhancement in radon transform space", Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); https://doi.org/10.1117/12.48395

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