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Target Tracking and Classification Using Compressive Measurements of MWIR and lwir Coded Aperture Cameras

Journal of Signal and Information Processing 2019年第3期10卷 73-95页

作者： Chiman Kwan Bryan Chou Jonathan Yang Akshay Rangamani Trac Tran Jack Zhang Ralph Etienne-Cummings Applied Research LLC Rockville Maryland USA Google Inc. Mountain View California USA Department of Electrical and Computer Engineering the Johns Hopkins University Baltimore USA Department of Electrical Engineering Massachusetts Institute of Technology Cambridge Massachusetts USA

Pixel-wise Code Exposure (PCE) camera is one type of compressive sensing camera that has low power consumption and high compression ratio. Moreover, a PCE camera can control individual pixel exposure time that can enable high dynamic range. Conventional approaches of using PCE camera involve a time consuming and lossy process to reconstruct the original frames and then use those frames for target tracking and classification. In this paper, we present a deep learning approach that directly performs target tracking and classification in the compressive measurement domain without any frame reconstruction. Our approach has two parts: tracking and classification. The tracking has been done using YOLO (You Only Look Once) and the classification is achieved using Residual Network (ResNet). Extensive experiments using mid-wave infrared (MWIR) and long-wave infrared (lwir) videos demonstrated the efficacy of our proposed approach.

关键词： Target Tracking Classification Compressive Sensing MWIR lwir YOLO ResNet Infrared Videos

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A compact polarization-integrated long wavelength infrared focal plane array based on In As/GaSb superlattice

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Science China(Information Sciences) 2022年第2期65卷 204-210页

作者： Jian ZHOU Yi ZHOU Ying SHI Fangfang WANG Zhicheng XU Zhizhong BAI Min HUANG Lulu ZHENG Zhaoming LIANG Yihong ZHU Qingqing XU Yiming SHEN Xiangxiao YING Jianxin CHEN Key Laboratory of Infrared Imaging Materials and Devices Shanghai Institute of Technical PhysicsChinese Academy of Sciences Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences

Real-time polarization imaging plays a vital role in target detection, recognition, and tracking in complex scenes. However, large optical crosstalk and the integration technology are difficult problems in the development of polarization-integrated infrared detectors. We demonstrate a monolithic long wavelength infrared(lwir) In As/Ga Sb superlattice focal plane array(FPA) integrated with the polarizer. To obtain high performance and real-time polarization imaging devices, the parameters of the grating were optimized and the optical crosstalk between adjacent polarization bands was studied. We analyze the light diffraction depending on the distance between the polarizer and photosensitive elements and the coupling between oblique incident light and device. The fabrication process of the antireflective polarizer, the integration technology of the polarizer and the FPA composed of 512×4×3 pixels were explored. Finally, a polarization integrated focal plane array(PI-FPA) was fabricated to detect polarized light with different oscillating directions. The large response extinction ratio of corresponding polarization bands was measured as 50:1,49:1, and 44:1 of 0?, 60?, and 120?, respectively.

关键词： lwir polarization integration infrared detector optical crosstalk extinction ration

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Deep Learning Based Target Tracking and Classification for Infrared Videos Using Compressive Measurements

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Journal of Signal and Information Processing 2019年第4期10卷 167-199页

作者： Chiman Kwan Bryan Chou Jonathan Yang Trac Tran Applied Research LLC Rockville MD USA Google Inc. Mountain View CA USA Department of Electrical and Computer Engineering The Johns Hopkins University Baltimore MD USA

Although compressive measurements save data storage and bandwidth usage, they are difficult to be used directly for target tracking and classification without pixel reconstruction. This is because the Gaussian random matrix destroys the target location information in the original video frames. This paper summarizes our research effort on target tracking and classification directly in the compressive measurement domain. We focus on one particular type of compressive measurement using pixel subsampling. That is, original pixels in video frames are randomly subsampled. Even in such a special compressive sensing setting, conventional trackers do not work in a satisfactory manner. We propose a deep learning approach that integrates YOLO (You Only Look Once) and ResNet (residual network) for multiple target tracking and classification. YOLO is used for multiple target tracking and ResNet is for target classification. Extensive experiments using short wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (lwir) videos demonstrated the efficacy of the proposed approach even though the training data are very scarce.

关键词： Target Tracking Classification Compressive Sensing SWIR MWIR lwir YOLO ResNet Infrared Videos

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在分子束外延P型HgCdTe薄膜上制造长波红外平面光电二极管

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红外 1998年第10期19卷 17-23页

作者： V.N.Ovsyuk 顾聚兴俄罗斯半导体物理研究所

本文介绍分子束外延生长HgCdTe外延层以及利用平面工艺技术制造敏感波长为8μm-10μm的小型p-n结的结果。在分子束外延过程中,生长动态、组分和表面粗糙度是利用内在的高能电子衍射计和椭圆对称计在原位控制的。小面积光敏二极管(50×7... 详细信息

本文介绍分子束外延生长HgCdTe外延层以及利用平面工艺技术制造敏感波长为8μm-10μm的小型p-n结的结果。在分子束外延过程中,生长动态、组分和表面粗糙度是利用内在的高能电子衍射计和椭圆对称计在原位控制的。小面积光敏二极管(50×70μm)是利用平面工艺技术和阳极氧化物薄膜下的退火技术而制造出来的。V-Ⅰ、光谱响应以及噪声特性的测量结果表明,在用分子束外延技术生长的碲镉汞外延层上制造的光电二极管具有可以接受的参数,用这种器件可以制造一维和二维光电二极管列阵。

关键词： lwir 长波红外光电二极管汞镉碲

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新型Si基长波红外探测器SiGe／Si异质结内光电发射探测器

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红外 1992年第3期13卷 8-12页

作者： Lin,TL 陆玮

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