首页> 外文会议>Conference on Automatic Target Recognition XIV; 20040413-20040415; Orlando,FL; US >Image Super-Resolution for Improved Automatic Target Recognition
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Image Super-Resolution for Improved Automatic Target Recognition

机译:图像超分辨率可改善自动目标识别

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摘要

Infrared imagers used to acquire data for automatic target recognition are inherently limited by the physical properties of their components. Fortunately, image super-resolution techniques can be applied to overcome the limits of these imaging systems. This increase in resolution can have potentially dramatic consequences for improved automatic target recognition (ATR) on the resultant higher-resolution images. We will discuss super-resolution techniques in general and specifically review the details of one such algorithm from the literature suited to real-time application on forward-looking infrared (FLIR) images. Following this tutorial, a numerical analysis of the algorithm applied to synthetic IR data will be presented, and we will conclude by discussing the implications of the analysis for improved ATR accuracy.
机译:用于获取数据以进行自动目标识别的红外成像仪固有地受到其组件物理特性的限制。幸运的是,可以应用图像超分辨率技术来克服这些成像系统的限制。分辨率的提高可能会对最终的高分辨率图像上改进的自动目标识别(ATR)产生潜在的巨大影响。我们将讨论一般的超分辨率技术,并从适用于前瞻性红外(FLIR)图像实时应用的文献中详细审查一种算法的细节。在完成本教程之后,将对应用于合成红外数据的算法进行数值分析,并通过讨论分析对提高ATR准确性的意义进行总结。

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