FLIR range performance predictions using synthetic imagery

Eddie L. Jacobs; David L. Wilson

doi:10.1117/12.391773

17 July 2000 FLIR range performance predictions using synthetic imagery

Eddie L. Jacobs, David L. Wilson

Proceedings Volume 4030, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XI; (2000) https://doi.org/10.1117/12.391773
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

Traditional FLIR performance analysis uses analytic models to predict sensor performance characteristics such as modulation transfer function (MTF) and minimum resolvable temperature (MRT). These characteristics are then used in conjunction with empirical criterion such as the Johnson cycle criteria to predict the performance of observers using the modeled sensor. In general, such an analysis suffers from inadequate descriptions of the effects of the background and incomplete descriptions of the observer detection mechanism. Accurate predictions of field performance in a particular setting require the expensive collection of imagery for metric analysis or perception tests. In this paper, an image-based approach is investigated. Using an advanced FLIR simulation, synthetic image sets are generated under controlled conditions. Using these image sets, image metrics are calculated and predictions of target detectability are made using a contrast-to-clutter model and a computational vision model. These predictions are compared to results obtained using a traditional range performance analysis from the MRT based ACQUIRE model. An assessment of the advantages and disadvantages of the image-based approach is given.

Citation Download Citation

Eddie L. Jacobs and David L. Wilson "FLIR range performance predictions using synthetic imagery", Proc. SPIE 4030, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XI, (17 July 2000); https://doi.org/10.1117/12.391773

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available