Abstract. We are using active infrared (IR) spectroscopic imaging to detect trace explosives on surfaces at proximal distances up to a few meters. The technology comprises an IR quantum cascade laser (QCL) for illumination and an IR focal plane array (FPA) sensor to collect signal backscattered from surfaces of interest. By sweeping the wavelength of the QCL while collecting image frames with the FPA, we generate an active hyperspectral image (HSI) cube. The HSI cube contains both spatial and spectral information, where the spectrum of a pixel, or region of interest within the image, can be extracted and compared against a known threat library. These cubes are fed into a convolutional neural network (CNN) trained on purely synthetic data to identify chemicals in the field of view. The CNN identifies chemicals by their IR signature and identifies their location within the image.

中文翻译：

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使用主动红外后向散射光谱法检测痕量爆炸物的高光谱成像

摘要。我们正在使用主动红外 (IR) 光谱成像来检测几米近距表面上的痕量爆炸物。该技术包括用于照明的红外量子级联激光器 (QCL) 和用于收集从感兴趣的表面反向散射的信号的红外焦平面阵列 (FPA) 传感器。通过在使用 FPA 收集图像帧的同时扫描 QCL 的波长，我们生成了一个活动的高光谱图像 (HSI) 立方体。HSI 立方体包含空间和光谱信息，其中可以提取像素或图像中感兴趣区域的光谱，并将其与已知威胁库进行比较。这些立方体被送入一个卷积神经网络 (CNN)，在纯合成数据上进行训练，以识别视野中的化学物质。