Correlation filter fusion for detection:  morphological, wavelet, and Gabor methods

David P. Casasent; John Scott Smokelin; Anqi Ye; Roland H. Schaefer

doi:10.1117/12.163562

9 November 1993 Correlation filter fusion for detection: morphological, wavelet, and Gabor methods

David P. Casasent, John Scott Smokelin, Anqi Ye, Roland H. Schaefer

Proceedings Volume 2026, Photonics for Processors, Neural Networks, and Memories; (1993) https://doi.org/10.1117/12.163562
Event: SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, 1993, San Diego, CA, United States

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 (P_D). We fuse the results from different outputs to reduce false alarms (P_FA). All filters are realizable on a correlator.

Citation Download Citation

David P. Casasent, John Scott Smokelin, Anqi Ye, and 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); https://doi.org/10.1117/12.163562

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