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Proceedings Paper

Correlation filter design using a single cluttered training image for detecting a noisy target in a nonoverlapping scene
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Paper Abstract

Classical correlation filters for object detection and location estimation are designed under the assumption that the shape and intensity values of the object of interest are explicitly known. In this work we assume that the target is given at unknown coordinates in a reference image with a cluttered background corrupted by additive noise. We consider the nonoverlapping signal model for both the reference image and the input scene. Optimal correlation filters, with respect to signal-to-noise ratio and peak-to-output energy, for object detection and location estimation are derived. Estimation techniques are proposed for the parameters required for filter design. Computer simulation results obtained with the proposed filters are presented and compared with those of common correlation filters.

Paper Details

Date Published: 21 August 2010
PDF: 8 pages
Proc. SPIE 7798, Applications of Digital Image Processing XXXIII, 779806 (21 August 2010); doi: 10.1117/12.860215
Show Author Affiliations
Pablo Mario Aguilar-González, Ctr. de Investigación Científica y de Educación Superior de Ensenada (Mexico)
Vitaly Kober, Ctr. de Investigación Científica y de Educación Superior de Ensenada (Mexico)


Published in SPIE Proceedings Vol. 7798:
Applications of Digital Image Processing XXXIII
Andrew G. Tescher, Editor(s)

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