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Proceedings Paper

Simple algorithm for cluster detection
Author(s): James J. Magee
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Paper Abstract

A simple algorithm for the detection of a cluster of faint point signals in noise is described. The algorithm, which uses the properties of the amplitude statistics of the data, appears sufficiently robust so as to be applicable to a wide range of cases. Because the algorithm is not computationally intensive, it can be implemented with a small amount of hardwired logic and/or a simple microprocessor. It can also be used to supplement other more conventional cluster algorithms. Examples are shown using 15 to 50 points within a cluster area of 400 pixels. SNR for the individual points ranges between 1.0 and 2.5. For these examples, the algorithm improves the probabilities of detection and false detection and is equivalent to an increase in point signal SNR by a factor of 2 to 3.

Paper Details

Date Published: 13 April 1993
PDF: 9 pages
Proc. SPIE 1838, 21st AIPR Workshop on Interdisciplinary Computer Vision: An Exploration of Diverse Applications, (13 April 1993); doi: 10.1117/12.142795
Show Author Affiliations
James J. Magee, Lockheed Missiles & Space Co., Inc. (United States)


Published in SPIE Proceedings Vol. 1838:
21st AIPR Workshop on Interdisciplinary Computer Vision: An Exploration of Diverse Applications

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