9 November 1993 Correlation filter fusion for detection: morphological, wavelet, and Gabor methods
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Abstract
We consider the detection of candidate objects (regions of interest) in a scene containing high clutter, multiple objects in different classes, independent of aspect view, with hot/cold/bimodal/partial object variations, and with low contrast targets. We use three different filters with each designed to produce high probability of detection (PD). We fuse the results from different outputs to reduce false alarms (PFA). All filters are realizable on a correlator.
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David P. Casasent, John Scott Smokelin, Anqi Ye, Roland H. Schaefer, "Correlation filter fusion for detection: morphological, wavelet, and Gabor methods", Proc. SPIE 2026, Photonics for Processors, Neural Networks, and Memories, (9 November 1993); doi: 10.1117/12.163562; https://doi.org/10.1117/12.163562
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KEYWORDS
Detection and tracking algorithms

Databases

Target detection

Image filtering

Linear filtering

Wavelets

Selenium

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