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Optical Engineering

Optimal Detection Of Object Boundaries In Uncorrelated Speckle
Author(s): Alan C. Bovik; David C. Murson
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Paper Abstract

We describe several techniques for detecting object boundaries in images immersed in speckle noise. Based on the assumption that the image speckle is uncorrelated, optimal statistical procedures are formulated using local tests for changes in intensity. The first method described is parametric: the average values taken from adjacent image neighborhoods are ratioed and compared to a threshold statistic. A cooperative scheme is then described in which the parametric statistic is applied only at the zero crossings of the image resulting from a convolution with a narrowband differential operator. A non-parametric procedure based on a linear rank statistic is also described, which can be shown to be locally most powerful (among rank tests) under the noise assumption. Examples illustrate the effectiveness of each method.

Paper Details

Date Published: 1 November 1986
PDF: 7 pages
Opt. Eng. 25(11) 251246 doi: 10.1117/12.7973989
Published in: Optical Engineering Volume 25, Issue 11
Show Author Affiliations
Alan C. Bovik, The University of Texas at Austin (United States)
David C. Murson, University of Illinois (United States)

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