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

Abstract

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.

Effectiveness assessment of signal processing in the presence of smear

“…The results are in agreement with the general finding [3][4][5][6][7][8] that motion with under-sampled cameras can significantly increase observer performance and at the same time provide a quantitative explanation for the marginal performance difference between the identification of hand-held objects in static and dynamic imagery reported by Beintema et al 9 As explained, the latter is the only study performed with an uncooled thermal imager moving at a speed of 0.57 pixel∕ frame, hence the results are considerably affected by detector smear.…”

“…For the dynamic recordings, the radius of the circular motion was approximately four pixels or 5.2 mrad (this is slightly different from the experiments by Bijl et al 5 and Beintema et al 9 ), and rotation frequency was varied in such a way that the velocity of the TCAT over the sensor focal plane array was 0, 0. …”

“…The setup is similar to the one used by Bijl et al 5 and Beintema et al 9 except for some minor differences that will be indicated in the text below.…”

“…As in the study of Beintema et al, 9 test patterns were shown on a 22-inch computer CRT set at a resolution of 1024 by 768 pixels. The display differs in size and resolution from the one used in the study by Bijl.…”

Sensor performance as a function of sampling (d) and optical blur (Fλ)

“…See Table 2. The FLIR SC2000 uncooled microbolometer is extensively investigated and data with the real and simulated sensor are reported in a series of papers 15,17,18 . The other sensors were selected from Krapels et al (2007) 2 .…”