A ground truth tool for Synthetic Aperture Radar (SAR) imagery

I. Pavlidis, Douglas P. Perrin, N. Papanikolopoulos, W. Au, S. Sawtelle
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Abstract

The performance of computer vision algorithms has made great strides and it is good enough to be useful in a number of civilian and military applications. Algorithm advancement in Automatic Target Recognition (ATR) in particular; has reached a critical point. State-of-the-art ATRs are capable of delivering robust performance for certain operational scenarios. As Computer Vision technology matures and algorithms enter the civilian and military marketplace as products, the lack of a formal testing theory and tools become obvious. In this paper we present the design and implementation of a Ground Truth Tool (GTT) for Synthetic Aperture Radar (SAR) imagery. The tool serves as part of an evaluation system for SAR ATRs. It features a semi-automatic method for delineating image objects that draws upon the theory of deformable models. In comparison with other deformable model implementations, our version is stable and is supported by an extensive Graphical User Interface (GUI). Preliminary experimental tests show that the system can substantially increase the productivity and accuracy of the image analyst (IA).
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合成孔径雷达(SAR)图像的地面真值工具
计算机视觉算法的性能已经取得了很大的进步,它足以在许多民用和军事应用中发挥作用。特别是自动目标识别(ATR)中的算法进展已经到了一个临界点。最先进的atr能够为某些操作场景提供强大的性能。随着计算机视觉技术的成熟和算法作为产品进入民用和军用市场,缺乏正式的测试理论和工具变得明显。本文介绍了合成孔径雷达(SAR)图像的地面真值工具(GTT)的设计和实现。该工具是SAR atr评估系统的一部分。它的特点是利用可变形模型的理论来描绘图像对象的半自动方法。与其他可变形模型实现相比,我们的版本是稳定的,并且得到了广泛的图形用户界面(GUI)的支持。初步的实验测试表明,该系统可以大大提高图像分析(IA)的生产率和准确性。
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