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

机译:目标采集性能:目标方向角度,动态成像和信号处理的影响

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In an extensive Target Acquisition (TA) performance study, we recorded static and dynamic imagery of a set of militaryand civilian two-handheld objects at a range of distances and aspect angles with an under-sampled uncooled thermalimager. Next, we applied signal processing techniques including DSR (Dynamic Super Resolution) and LACE (LocalAdaptive Contrast Enhancement) to the imagery. In a perception experiment, we determined identification (ID) andthreat/non-threat discrimination performance as a function of target range for a variety of conditions. The experimentwas performed to validate and extend current TA models. In addition, range predictions were performed with two TAmodels: the TOD model and NVThermIP. The results of the study are: i) target orientation has a strong effect onperformance, ii) the effect of target orientation is well predicted by the two TA models, iii) absolute identification rangeis close the range predicted with the two models using the recommended criteria for two-handheld objects, iv) there wasno positive effect of sensor motion on performance, and this was against the expectations based on earlier studies, v) thebenefit of DSR was smaller than expected on the basis of the model predictions, and vi) performance with LACE wassimilar to performance on an image optimized manually, indicating that LACE can be used to optimize the contrastautomatically. The relatively poor results with motion and DSR are probably due to motion smear induced by a highercamera speed than used in earlier studies. Camera motion magnitude and smear are not yet implemented in TA models.
机译:在广泛的目标习得(TA)绩效研究中,我们在一系列距离和方面角度的一系列距离的距离和动态图像的静态和动态图像记录了一组距离的距离和方向角度。接下来,我们应用了信号处理技术,包括DSR(动态超分辨率)和蕾丝(本地active对比度增强)到图像。在感知实验中,我们确定了识别(ID)andthreat /非威胁歧视性能作为各种条件的目标范围的函数。进行实验支持,以验证和延长当前的TA模型。此外,使用两个Tamodels进行范围预测:TOD模型和NVThermip。研究结果是:i)目标方向具有强烈的效果,ii)目标取向的效果通过两个TA模型,III)绝对识别范围缩放使用推荐标准预测的范围预测。对于双手持物体,IV),传感器运动对性能的存在积极影响,这与基于早期研究的期望,V)DSR的非基础比模型预测和VI)的表现小于预期蕾丝WASSIMILAR在手动优化的图像上进行性能,表明鞋带可用于优化对比度。与运动和DSR的运动和DSR的结果相对较差,可能是由于早期研究中使用的高舒适速度引起的运动污迹。 TA型号尚未实现相机运动幅度和涂片。

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