Real-time, short-wave, infrared hyperspectral conforming imaging sensor for the detection of threat materials
Real-time, short-wave, infrared hyperspectral conforming imaging sensor for the detection of threat materials
复制标题
用于检测威胁材料的实时、短波、红外高光谱合格成像传感器
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
M. Hebert
中科院分区：
文献类型：
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作者：
M. Nelson;Shawna K. Tazik;P. Treado;Tiancheng Zhi;S. Narasimhan;B. Pires;M. Hebert
人们越来越需要在安全距离内以高度自主的方式实时有效检测危险材料。为了满足这一需求，化学图像传感器系统（CISS）与卡内基梅隆机器人研究所合作开发了一种新颖的、适应性强的短波红外（SWIR）高光谱成像系统，用于危险材料（例如，爆炸物、麻醉品等）。该系统的核心是共形滤波器（CF），它是一种基于液晶（LC）的可调谐滤波器，可传输多频带波形。基于多元光学计算的概念，CF被电光地和动态地调谐以模仿用于分类的判别向量的功能。所得到的集成检测器响应近似于传统的高光谱成像的检测响应，仅具有两个离散的测量值，而不是数百到数千个。实时检测是通过在双偏振（DP）系统内串联操作两个CF来实现的，该系统利用LC滤波器的偏振灵敏度，并允许同时采集压缩的高光谱图像。这种改进的采样率与高级对象识别、语义场景理解和图像重建算法相结合，使得能够实时（即，>10检测fps），在移动中检测目标。本文将讨论第一代SWIR DP-CF成像传感器的开发、特性和测试结果，重点介绍其在爆炸物和毒品威胁检测中的应用。
There is a growing demand for effective detection of hazardous materials at safe distances in real-time with a high degree of autonomy. In an effort to address this need, ChemImage Sensor Systems (CISS) in collaboration with the Carnegie Mellon Robotics Institute has developed a novel, adaptable, short-wave infrared (SWIR) hyperspectral imaging system for real-time standoff detection of hazardous materials (e.g., explosives, narcotics, etc.). At the heart of this system is the Conformal Filter (CF), which is a liquid crystal (LC)-based tunable filter that transmits multi-band waveforms. Building on concepts of multivariate optical computing, the CF is tuned electro-optically and dynamically to mimic the functionality of a discriminant vector for classification. The resulting integrated detector response approximates the detection response of conventional hyperspectral imaging with only two discrete measurements instead of hundreds to thousands. Real-time detection is achieved by operating two CFs in tandem within a dual polarization (DP) system, which exploits the polarization sensitivity of the LC filters and allows for simultaneous acquisition of the compressed hyperspectral imagery. This improved sampling rate coupled with advanced object recognition, semantic scene understanding, and image reconstruction algorithms enables real-time (i.e., >10 detection fps), on-the-move detection of targets. This paper will discuss the development, characterization, and test results of the first generation SWIR DP-CF imaging sensor, with a focus on its application to explosives and narcotic threat detection.