Statistical significance of features in digital images

Godtliebsen, F. ; Marron, J. S. ; Chaudhuri, Probal (2004) Statistical significance of features in digital images Image and Vision Computing, 22 (13). pp. 1093-1104. ISSN 0262-8856

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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. The usefulness of the new methodology is illustrated by the analysis of simulated and real images.

Item Type:Article
Source:Copyright of this article belongs to Elsevier Science.
Keywords:Kernel Smoothing; Curvature; Gradient; Scale Space; Statistical Significance; Sizer
ID Code:8115
Deposited On:26 Oct 2010 04:31
Last Modified:04 Feb 2011 05:07

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