Revised targeting task performance (TTP) metric for optical remote sensing system effectiveness evaluation

Die Hu; Xuxia Zhuang; Yun Wang

doi:10.1117/12.2651780

23 January 2023 Revised targeting task performance (TTP) metric for optical remote sensing system effectiveness evaluation

Die Hu, Xuxia Zhuang, Yun Wang

Author Affiliations +

Proceedings Volume 12557, AOPC 2022: Optical Sensing, Imaging, and Display Technology; 125571O (2023) https://doi.org/10.1117/12.2651780
Event: Applied Optics and Photonics China 2022 (AOPC2022), 2022, Beijing, China

Abstract

Target acquisition task-oriented effectiveness evaluation methods for optical remote sensing systems are helpful in the design phase to quantitatively evaluate and predict the target detection ability of optical remote sensing systems. Compared with the widely-used National Imagery Interpretability Rating Scale (NIIRS) and Johnson criteria, the Targeting Task Performance (TTP) metric has a more comprehensive evaluation model for electro-optical imaging systems, combined with the target features and human eye functions. This paper discussed the effects of the image luminance and noise distribution on the target acquisition task, and proposed a revised TTP metric, aiming at improving the accuracy of the effectiveness evaluation model. Aerial remote sensing experiments were carried out, and the ability of an optical remote sensing system to detect and recognize the target models was evaluated based on the proposed method. For aerial images under the NIIRS levels ranged from 2.98 to 4.43. The detection and recognition probabilities of aircraft models were calculated using the original and revised TTP metrics, respectively. It is inferred that the evaluation results by the revised TTP metric are in better accordance with the NIIRS level of the images.

Citation Download Citation

Die Hu, Xuxia Zhuang, and Yun Wang "Revised targeting task performance (TTP) metric for optical remote sensing system effectiveness evaluation", Proc. SPIE 12557, AOPC 2022: Optical Sensing, Imaging, and Display Technology, 125571O (23 January 2023); https://doi.org/10.1117/12.2651780

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