Significance in Scale Space

Abstract

This paper develops a methodology for finding which features in a noisy image are strong enough to be distinguished from background noise. It is based on scale space, i.e. a family of smooths of the image. Pixel locations having statistically significant gradient and/or curvature are highlighted by colored symbols. The gradient version is enhanced by displaying regions of significance with streamlines. Ideas are illustrated with simulated and real images.

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Cite this paper

@inproceedings{Godtliebsen2008SignificanceIS, title={Significance in Scale Space}, author={F. Godtliebsen and J. S. Marron and P. Chaudhuri}, year={2008} }