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Infrared object classification with a hybrid optical convolution neural network

APPLIED OPTICS 2021年第25期60卷 G224-G231页

作者： Chen, Jianbo Talley, Jennifer Kelly, Kevin F. Rice Univ Elect & Comp Engn Dept 6100 Main St Houston TX 77005 USA HID Global 611 Ctr Ridge Dr Austin TX 78753 USA Air Force Res Lab Eglin AFB FL 32542 USA

Recent advancements in machine vision have enabled a great range of applications from image classification to autonomous driving. However, there is still a dilemma between the pursuit of higher-resolution training images that require a detector array with more pixels on the front end, and the demands on acquisition for embedded systems restrained by power, transmission bandwidth, and storage. In this paper, a multi-pixel hybrid optical convolutional neural network machine vision system was designed and validated to perform high-speed infrared object detection. The proposed system replicates the front convolution layer in a convolutional neural network utilizing a high-speed digital micro-mirror device to display the first layer of kernels at a resolution greater than the subsequent detector. After this, further convolutions are carried out in software to perform the object recognition. An infrared vehicle dataset was used to validate the performance of the hybrid system through simulation. We also tested this in hardware by performing infrared classification on toy vehicles to showcase the feasibility of such a design. (C) 2021 optical Society of America

关键词： Detector arrays image compression Machine vision Neural networks Object detection signal processing

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Ultrafast machine vision with 2D material neural network image sensors

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NATURE 2020年第7797期579卷 62-+页

作者： Mennel, Lukas Symonowicz, Joanna Wachter, Stefan Polyushkin, Dmitry K. Molina-Mendoza, Aday J. Mueller, Thomas Vienna Univ Technol Inst Photon Vienna Austria

Machine vision technology has taken huge leaps in recent years, and is now becoming an integral part of various intelligent systems, including autonomous vehicles and robotics. Usually, visual information is captured by a frame-based camera, converted into a digital format and processed afterwards using a machine-learning algorithm such as an artificial neural network (ANN)(1). The large amount of (mostly redundant) data passed through the entire signal chain, however, results in low frame rates and high power consumption. Various visual data preprocessing techniques have thus been developed(2-7) to increase the efficiency of the subsequent signal processing in an ANN. Here we demonstrate that an image sensor can itself constitute an ANN that can simultaneously sense and process optical images without latency. Our device is based on a reconfigurable two-dimensional (2D) semiconductor(8,9) photodiode(10-12) array, and the synaptic weights of the network are stored in a continuously tunable photoresponsivity matrix. We demonstrate both supervised and unsupervised learning and train the sensor to classify and encode images that are optically projected onto the chip with a throughput of 20 million bins per second.

关键词： Electrical and electronic engineering optical properties and devices optoelectronic devices and components

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基于双螺旋点扩散函数工程的多焦点图像扫描显微

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物理学报 2021年第3期70卷 298-304页

作者：李四维林丹樱邹小慧张炜陈丹妮于斌屈军乐深圳大学物理与光电工程学院光电子器件与系统教育部/广东省重点实验室深圳518060 广东省科学院航空装备研究所珠海519000

在传统共聚焦显微技术的基础上,图像扫描显微技术使用面阵探测器来代替单点探测器,结合虚拟数字针孔并利用像素重定位和解卷积图像重构算法将传统宽场显微镜的分辨率提高一倍,实现了高信噪比的超分辨共焦成像.但是,由于采用逐点扫描的方... 详细信息

在传统共聚焦显微技术的基础上,图像扫描显微技术使用面阵探测器来代替单点探测器,结合虚拟数字针孔并利用像素重定位和解卷积图像重构算法将传统宽场显微镜的分辨率提高一倍,实现了高信噪比的超分辨共焦成像.但是,由于采用逐点扫描的方式,三维成像速度相对较慢,限制了其在活体样品成像中的应用.为了进一步提高图像扫描显微术的成像速度,本文提出了一种基于双螺旋点扩散函数工程的多焦点图像扫描显微成像方法和系统.在照明光路中,利用高速数字微镜器件产生周期分布的聚焦点阵对样品进行并行激发和快速二维扫描;在探测光路中,利用双螺旋相位片将激发点荧光信号的强度分布转换为双螺旋的形式;最终,利用后期数字重聚焦处理,从单次样品扫描数据中重构出多个样品层的超分辨宽场图像.在此基础上,利用搭建的系统分别对纤维状肌动蛋白和海拉细胞线粒体进行成像实验,证明了该方法的超分辨能力和快速三维成像能力.

关键词：图像扫描显微技术双螺旋点扩散函数共聚焦显微技术

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基于可调光延迟线的微波光子零中频接收机研究

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中国激光 2021年第9期48卷 113-121页

作者：梅理崇毓华朱宇鹏彭卫王冰中国电子科技集团公司第三十八研究所安徽合肥230000 安徽省天线与微波工程实验室安徽合肥230000

提出了一种基于可调光延迟线的微波光子正交解调技术,并基于该技术设计了微波光子零中频接收机。通过调节光延迟线实现本振信号的90°移相,并采用波分复用方法在共用的级联马赫-曾德尔调制器结构中实现两条正交链路的射频信号与本... 详细信息

提出了一种基于可调光延迟线的微波光子正交解调技术,并基于该技术设计了微波光子零中频接收机。通过调节光延迟线实现本振信号的90°移相,并采用波分复用方法在共用的级联马赫-曾德尔调制器结构中实现两条正交链路的射频信号与本振信号的混频,从而提高了光正交解调的幅相一致性。所设计的微波光子零中频接收机可对光正交解调之后的中频处理器件如光电探测器、滤波器以及模数转换器等引起的链路幅相不平衡进行数字补偿。经数字幅相失衡补偿后,微波光子零中频接收机在中心频率为12 GHz、瞬时带宽为4 GHz的工作频段内测得幅度不平衡小于0.4 dB,相位不平衡小于1.5°,镜频抑制度大于45 dB,最高镜频抑制度可达79 dB。

关键词：光通信微波光子宽带接收机零中频镜频抑制

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Triple coding empowered FDMA-CDMA mode high security CAOS camera

arXiv

引用

arXiv 2021年

作者： Riza, Nabeel A. Mazhar, Mohsin A. Photonic Information Processing Systems Laboratory School of Engineering University College Cork College Road Cork Ireland

For the first time, the hybrid triple coding empowered Frequency Division Multiple Access (FDMA)-Code Division Multiple Access (CDMA) mode of the CAOS (i.e., Coded Access optical Sensor) camera is demonstrated. Compared to the independent FDMA and CDMA modes, the FDMA-CDMA mode has a novel high security space-time-frequency triple signal encoding design for robust, faster, linear irradiance extraction at a moderately High Dynamic Range (HDR). Specifically, this hybrid mode simultaneously combines the linear HDR strength of the FDMA-mode Fast Fourier Transform (FFT) digital signal processing (DSP)-based spectrum analysis with the high signal-to-Noise Ratio (SNR) provided by the many simultaneous CAOS pixels photo-detection of the CDMA-mode. In particular, the demonstrated FDMA-CDMA mode with P FDMA channels provides a P times faster camera operation versus the equivalent linear HDR Frequency Modulation (FM)CDMA mode. Visible band imaging experiments using a digital Micromirror Device (DMD)-based CAOS camera operating in its passive light mode demonstrates a P=4 channels FDMA-CDMA mode, illustrating high quality image recovery of a calibrated 64 dB 6-patches HDR target versus the CDMA and FM-CDMA CAOS modes that limit dynamic range and speed, respectively. For the first time, demonstrated is the simultaneous dual image capture capability of the FDMA-CDMA mode using Silicon (Si) and Germanium (Ge) large area point photo-detectors allowing the capture of the Ultraviolet (UV) – Near Infrared (NIR) 350-1800 nm full spectrum. The active FDMA-CDMA mode CAOS camera operation is also demonstrated using P=3 LED light sources, each with its unique optical spectral content driven by its independent FDMA frequency. This illuminated target spectral signature matched active CAOS mode allows simultaneous capture of P images without the use of P time multiplexed slots operation tunable optical filter. Applications for such a FDMA-CDMA camera includes controlled light illumination foo

关键词： signal to noise ratio

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FDMA-CDMA Mode CAOS Camera Demonstration using UV to NIR Full Spectrum

arXiv

引用

arXiv 2021年

作者： Riza, Nabeel A. Mazhar, Mohsin A. Photonic Information Processing Systems Laboratory School of Engineering University College Cork Ireland

— For the first time, the hybrid Frequency Division Multiple Access (FDMA)-Code Division Multiple Access (CDMA) mode of the CAOS (i.e., Coded Access optical Sensor) camera is demonstrated. The FDMA-CDMA mode is a time-frequency double signal encoding design for robust and faster linear High Dynamic Range (HDR) image irradiance extraction. Specifically, it simultaneously combines the strength of the FDMA-mode linear HDR Fast Fourier Transform (FFT) digital signal processing (DSP)-based spectrum analysis with the CDMA-mode provided many simultaneous CAOS pixels high signal-to-Noise Ratio (SNR) photo-detection. The FDMA-CDMA mode with P FDMA channels provides a faster camera operation versus the linear HDR Frequency Modulation (FM)-CDMA mode. Visible band imaging experiments using a digital Micromirror Device (DMD)-based CAOS camera demonstrate a P=4 channels FDMA-CDMA mode high quality image recovery of a calibrated 64 dB 6-patches HDR target versus the CDMA and FM-CDMA CAOS modes that limit dynamic range and speed, respectively. Simultaneous dual image capture capability of the FDMA-CDMA mode is also demonstrated for the first time in Ultraviolet (UV) – Near Infrared (NIR) 350-1800 nm full spectrum using Silicon (Si) and Germanium (Ge) point photo-detectors. Copyright © 2021, The Authors. All rights reserved.

关键词： Cameras

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Design and simulation of image nonlinear processing relational preprocessor based on iterational sorting node

Design and simulation of image nonlinear processing relation...

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Conference on optical Sensors

作者： Krasilenko, Vladimir G. Lazarev, Alexander A. Nikitovich, Diana, V Vinnitsa Social Econ Inst 86-131 Kelestskaya Str UA-21021 Vinnitsa Ukraine Vinnitsa Natl Tech Univ Vinnitsa Ukraine

ISBN: (数字)9781510627239

ISBN: (纸本)9781510627239

In this paper, we propose a new iterative process of sorting an array of signals, which differs from the known structures of sorting signals by uniformity, versatility, which allows direct and inverse sorting of an array of analog or digital signals. The basic elements of the proposed sorting structures are simple relational nodes for analogue signals from sensor devices and cameras. Such elements can be implemented on a different element basis, including, on devices for selecting a maximum or minimum of two analog or digital signals, which are implemented, in one of the variants, on CMOS current mirrors and carry out the function of continuous logic limited difference. We offer optoelectronic implementation of such basic relational element and a homogeneous sorting structure on such elements, consisting of two layers and a multichannel sampling and holding device. Nine signals corresponding to a selection window of a matrix sensor are fed to this structure, we sort them in five iterative steps, and at the output we receive the signals sorted by the rank, which, using the code controlled programmable multiplexer, generates an output signal, corresponding to the selected rank. We evaluate the technical parameters of such a relational preprocessor for nonlinear signal processing in image processors, sorting networks, multichannel parallel type sensor, processing, and encoding systems. The base cells consist of no more than 20 CMOS 1.5 mu m transistors, the total power consumption of the sorting node on 10 continuously logical base cells (CL BC) is 2mW, the supply voltage is 1.8 divided by 3.3V, the range of an input photocurrent is 0.1 divided by 24 mu A, the conversion cycle is 10 mu s, but can be improved by selecting other transistors and some modifications of the circuits. Such mixed analog processor is modeled in PSpice OrCad. The paper considers results of design and modeling of CL BC based on photosensitive cells with an extended electronic circuit and current

关键词： analog relational preprocessor image nonlinear processing simulation continuous logic current mirror sorting networks methods of selection and rank preprocessing rank filtering

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Design of neuron-calculators for the normalized equivalence of two matrix arrays based on FPGA for self-learning equivalently convolutional neural networks (SLE_CNNs)

Design of neuron-calculators for the normalized equivalence ...

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Conference on Real-Time image processing and Deep Learning

作者： Krasilenko, Vladimir G. Lazarev, Alexander A. Nikitovich, Diana, V Vinnytsia Social Econ Inst 86-131 Kelestskaya Str UA-21021 Vinnytsia Ukraine Vinnytsia Natl Tech Univ Vinnytsia Ukraine

ISBN: (纸本)9781510626584

First, in the introduction, we will show the urgent need to create neuron-calculators (NCs) for the normalized equivalence of two matrix arrays for self-learning equivalently-convolutional neural networks (SLE_CNNs), video processors for parallel image processing with enhanced functionality. Consider promising areas of application of such single and multichannel neuron-calculators as high-precision, high-speed and high-performance accelerators for hardware systems and architectures for recognition, classification, image categorization, in particular for 2D-image space-invariant associative memory structures, SLE_CNNs based on the equivalence paradigm. Next, we will consider and analyze the theoretical foundations, the mathematical apparatus of matrix and continuous logic, and their basic operations, show their functional completeness, evaluate their advantages and prospects for application in the design of biologically inspired devices and systems for processing and analyzing signal arrays. We will show that some functions of continuous logic, including operations of normalized equivalence of vector and matrix signals, operation of the bounded difference of continuous logic, are the powerful basis for designing advanced accelerator calculators, micro-cells for hybrid ( mixed) analog-to-digital transformations, comparisons and calculations of characteristics. Next, we will consider in more detail the design and simulation aspects of such digital neuron-calculators for the normalized equivalence of two matrix arrays based on FPGA, including their various modifications, depending on the dimension and the number of compared arrays. We will propose our approach for calculation of the normalized equivalence functions comparing current fragments of images and filters with dimensions 3x3, 7x7, 15x15 and others. The project is executed on FPGA ALTERA MAXII. The simulation was done with Intel Quartus Prime 17 and showed that in a single chip it is possible to place four paral

关键词： self-learning convolutional neural networks optoelectronic neuron-equivalentor current mirror equivalent models continuous-logical operations 2D spatial function accelerator learning nonlinear processing

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verification of the accuracy of a hybrid breast imaging simulation framework for virtual clinical trial applications (vol 7, 042804, 2020)

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JOURNAL OF MEDICAL IMAGING 2020年第6期7卷 042804页

作者： Vancoillie, Liesbeth Marshall, Nicholas Cockmartin, Lesley Vignero, Janne Zhang, Guozhi Bosmans, Hilde Katholieke Univ Leuven Dept Imaging & Pathol Div Med Phys & Qual Assessment Leuven Belgium UZ Leuven Dept Radiol Leuven Belgium

Purpose: The impact of system parameters on signal detectability can be studied with simulation platforms. We describe the steps taken to verify and confirm the accuracy of a local platform developed for the use in virtual clinical trials. Approach: The platform simulates specific targets into existing two-dimensional full-field digital mammography and digital breast tomosynthesis images acquired on a Siemens Inspiration system. There are three steps: (1) creation of voxel models or analytical objects; (2) generation of a realistic object template with accurate resolution, scatter, and noise properties; and (3) insertion and reconstruction. Four objects were simulated: a 0.5-mm aluminium (Al) sphere and a 0.2-mm-thick Al sheet in a PMMA stack, a 0.8-mm steel edge and a three-dimensional mass model in a structured background phantom. Simulated results were compared to acquired data. Results: Peak contrast and signal difference-to-noise ratio (SDNR) were in close agreement (<5 % error) for both sphere and sheet. The similarity of pixel value profiles for sphere and sheet in the xy direction and the artifact spread function for real and simulated spheres confirmed accurate geometric modeling. Absolute and relative average deviation between modulation transfer function measured from a real and simulated edges showed accurate sharpness modelling for spatial frequencies up to the Nyquist frequency. Real and simulated objects could not be differentiated visually. Conclusions: The results indicate that this simulation framework is a strong candidate for use in virtual clinical studies.

关键词： digital breast tomosynthesis Modulation transfer functions optical spheres Aluminum Breast imaging image processing 3D modeling Photovoltaics Polymethylmethacrylate Imaging systems

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Backscattering-Immune Computing of Spatial Differentiation by Nonreciprocal Plasmonics

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Physical Review Applied 2019年第5期11卷 054033-054033页

作者： Weixuan Zhang Xiangdong Zhang Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurements Ministry of Education Beijing Key Laboratory of Nanophotonics and Ultrafine Optoelectronic Systems School of Physics Beijing Institute of Technology Beijing 100081 China

Spatial differentiation is a fundamental mathematical operation used in many ﬁelds of science or engineering. Recently, optical analog computing of spatial differentiation, which can overcome the speed and energy limitations of digital differentiation techniques, has been realized in some nano systems such as the excitation of surface plasmon polaritons (SPPs). However, the inevitable backscattering of SPP propagation around defects or discontinuities may bring some undesired noises to the output signal. In this work, we firstly design a backscattering-immune spatial differentiator with the utilization of the nonreciprocal plasmonic platform, where the topologically protected one-way SPP leaky mode exists, in the terahertz (THz) region. Guided by the nonreciprocal spatial coupled-mode theory, we show that the ideal transfer function of the first-order spatial differentiation is able to be realized by subtly tuning the balance between the asymmetric leaky rate stemming from the nonreciprocal nature and intrinsic absorption rate of the system. Full wave simulations show that the first-order differentiation without backscattering around defects can be precisely implemented by using the designed nonreciprocal differentiator. Our proposed backscattering-immune spatial differentiator can find widespread applications for robust edge detection and image processing in the THz frequency range.

关键词： Nanophotonics Plasmonics Surface plasmon polariton Topological effects in photonic systems Devices Imaging & optical processing Terahertz techniques

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