<title>Dual-band FLIR fusion for target detection</title>

Abstract

Passive infrared imagers have long been used to detect military targets in operational scenarios. The proliferation of sensors on the battlefield has increased the need for automatic detection algorithms with low false alarm rates and high detection rates. Most infrared imagers currently operate in a single band. We are investigating the utility of dualband passive infrared sensors for target detection, and attempting to quantify the performance improvement over single band sensors. The two bands used in this research were broadband longwave and broadband midwave. The performance differences were observed using a similar set of neural-based target detectors, each of which consists of an eigenspace transformation and a simple multilayer perceptron (MLP) with different inputs. The detectors were trained with midwave-only, longwave-only, as well as signal-level and feature-level dualband inputs. Experimental results indicate significant performance improvement by the dualband inputs over single band data.