Automatic target recognition using Karhunen-Loeve transform-generated `eigenimages`

Brian D. Singstock; Steven K. Rogers; Matthew Kabrisky; Dennis W. Ruck

doi:10.1117/12.138230

9 July 1992 Automatic target recognition using Karhunen-Loeve transform-generated `eigenimages`

Brian D. Singstock, Steven K. Rogers, Matthew Kabrisky, Dennis W. Ruck

Proceedings Volume 1699, Signal Processing, Sensor Fusion, and Target Recognition; (1992) https://doi.org/10.1117/12.138230
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

Most automatic target recognition (ATR) systems are based upon measuring a set of predetermined features someone has decided will separate the classes of targets from one another. However, this system requires the user to decide what features will work best. Maybe it would be best to look at the targets and decide what is different between them. This is the motivation behind taking the Karhunen-Loeve Transform (KLT) of the images. The KLT finds the most variance between the images thus leaving to the computer the decision of where the difference between the targets lies. In this paper, two approaches to feature generation for target classification of infrared images are addressed: a standard feature set approach, and a KLT approach. Each method is explained and results are included.

Citation Download Citation

Brian D. Singstock, Steven K. Rogers, Matthew Kabrisky, and Dennis W. Ruck "Automatic target recognition using Karhunen-Loeve transform-generated `eigenimages`", Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); https://doi.org/10.1117/12.138230

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