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Target acquisition performance : Effects of target aspect angle, dynamic imaging and signal processing

Author: Beintema, J.A. · Bijl, P. · Hogervorst, M.A. · Dijk, J.
Publisher: SPIE
Place: Bellingham, WA
Institution: TNO Defensie en Veiligheid
Source:Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XIX, 18 March 2008 through 19 March 2008, Orlando, FL,, 6941
Proceedings of SPIE - The International Society for Optical Engineering
Identifier: 240851
doi: doi:/10.1117/12.777561
Article number: 69410C
Keywords: Dynamic imaging · Image enhancement · Local adaptive contrast enhancement · NVThermIP · Sensor performance · Super resolution · Target acquisition · TOD · Validation · Digital cameras · Imaging techniques · Mathematical models · Military applications · Signal processing


In an extensive Target Acquisition (TA) performance study, we recorded static and dynamic imagery of a set of military and civilian two-handheld objects at a range of distances and aspect angles with an under-sampled uncooled thermal imager. Next, we applied signal processing techniques including DSR (Dynamic Super Resolution) and LACE (Local Adaptive Contrast Enhancement) to the imagery. In a perception experiment, we determined identification (ID) and threat/non-threat discrimination performance as a function of target range for a variety of conditions. The experiment was performed to validate and extend current TA models. In addition, range predictions were performed with two TA models: the TOD model and NVThermIP. The results of the study are: i) target orientation has a strong effect on performance, ii) the effect of target orientation is well predicted by the two TA models, iii) absolute identification range is close the range predicted with the two models using the recommended criteria for two-handheld objects, iv) there was no positive effect of sensor motion on performance, and this was against the expectations based on earlier studies, v) the benefit of DSR was smaller than expected on the basis of the model predictions, and vi) performance with LACE was similar to performance on an image optimized manually, indicating that LACE can be used to optimize the contrast automatically. The relatively poor results with motion and DSR are probably due to motion smear induced by a higher camera speed than used in earlier studies. Camera motion magnitude and smear are not yet implemented in TA models.