<title>Application of synthetic imagery to target detection algorithm research</title>

Abstract

A multispectral modeling methodology has been developed by Nichols Research Corporation (NRC) in support of the Joint Mine Detection Technology Program at Coastal Systems Station, Panama City, FL. The modeling technique is an extension of NRC's Minefield Image Synthesis Tool. Synthetic imagery generated using this methodology has been compared to measured imagery with excellent results. Multispectral images from an intensified multispectral camera being flown over a minefield have been synthetically generated. This sequence of images was processed by NRC's baseline mine detection algorithm. The results were compared to images generated during a flight test. The conclusion is that the model can predict the automatic target recognition (ATR) algorithm's performance. This paper describes the minefield signature modeling methodology, presents a case study of the comparison of a synthetic scene and a measured scene, and indicates the lessons learned about the phenomenological causes of the mine and background signatures and their effects on a particular class of mine detection algorithms.