作者单位
摘要
1 南京理工大学电子工程与光电技术学院,江苏 南京 210094
2 南京理工大学理学院,江苏 南京 210094
传统激光超声合成孔径聚焦技术(LU-SAFT)通常需要在待测样品表面以小步长扫描来提高横向分辨率,但小扫描步长会导致总检测时间过长,影响检测效率。针对这一问题,笔者提出了基于压缩感知的LU-SAFT方法,以提升扫描效率。该方法首先使用压缩感知根据稀疏扫描点处A扫信号的最大强度恢复出全场的扫描点A扫信号最大强度,进而确定样品表面的最优扫描区域,然后在最优扫描区域内进行扫描,最后对缺陷进行SAFT图像重建。在实验中,笔者采用脉冲激光在含有缺陷的样品表面激发超声,使用激光多普勒测振仪探测超声,并利用基于压缩感知的LU-SAFT方法对样品内部缺陷进行检测,以验证所提方法的可行性。实验结果显示:针对相同的扫描区域,传统LU-SAFT需要扫查500个点,花费3.15 min;与传统LU-SAFT相比,本文所提方法在扫描点数上减少了80%,在扫描时间上缩短了80%,并且缺陷的SAFT成像信噪比提高了约42%。本文研究内容及结果可为激光超声无损检测提供更快速的检测方案。
激光光学 压缩感知 合成孔径聚焦技术 激光超声 缺陷检测 laser optics compressed sensing synthetic aperture focusing technology laser ultrasonic defect detection 
中国激光
2024, 51(2): 0201004
Author Affiliations
Abstract
1 Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai 200241, China
2 Engineering Center of SHMEC for Space Information and GNSS, East China Normal University, Shanghai 200241, China
A sub-Nyquist radar receiver based on photonics-assisted compressed sensing is proposed. Cascaded dictionaries are applied to extract the delay and the Doppler frequency of the echo signals, which do not need to accumulate multiple echo periods and can achieve better Doppler accuracy. An experiment is performed. Radar echoes with different delays and Doppler frequencies are undersampled and successfully reconstructed to obtain the delay and Doppler information of the targets. Experimental results show that the average reconstruction error of the Doppler frequency is 5.33 kHz using an 8-μs radar signal under the compression ratio of 5. The proposed method provides a promising solution for the sub-Nyquist radar receiver.
compressed sensing dictionary learning sub-Nyquist radar microwave photonics Doppler frequency 
Chinese Optics Letters
2024, 22(1): 013902
作者单位
摘要
五邑大学 智能制造学部, 广东 江门 529000
在超快时间尺度上以二维空间分辨率揭示激光脉冲在光刻胶之间的运动过程,将有助于了解激光加工过程和优化加工工艺。然而现有记录激光脉冲在光刻胶中运动过程的成像技术都存在需要多次重复拍摄或时间分辨率受限等问题。为了克服这些问题,通过使用压缩超快摄影来观测光刻胶中激光脉冲的运动。实验结果表明,搭建的实验系统能以1.54×1011fps的帧率,单次成像数百帧的图像序列深度,实时观测到这一不可重复的超快事件。
超快成像 压缩感知技术 飞秒激光脉冲 光刻胶 ultrafast imaging compressed sensing technique femtosecond laser pulse photoresist 
光学技术
2023, 49(3): 264
Author Affiliations
Abstract
Institut für Technische Optik, Universität Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
We propose a time-gated-single-pixel-camera as a promising sensor for image-free object detection for automotive application in adverse weather conditions. By combining the well-known principles of time-gating and single-pixel detection with neural networks, we aim to ultimately detect objects within the scene rapidly and robustly with a low-cost sensor. Here, we evaluate the possible data reduction such a system can provide compared to a conventional time-gated camera.
Time gating Single pixel camera Compressed sensing Neural networks 
Journal of the European Optical Society-Rapid Publications
2023, 19(1): 2023023
Yan Cai 1Shijian Li 1Wei Zhang 1Hao Wu 1[ ... ]Qing Zhao 1,2,**
Author Affiliations
Abstract
1 Center for Quantum Technology Research and Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurements (MOE), School of Physics, Beijing Institute of Technology, Beijing 100081, China
2 Beijing Academy of Quantum Information Sciences, Beijing 100193, China
Hadamard single-pixel imaging is an appealing imaging technique due to its features of low hardware complexity and industrial cost. To improve imaging efficiency, many studies have focused on sorting Hadamard patterns to obtain reliable reconstructed images with very few samples. In this study, we propose an efficient Hadamard basis sampling strategy that employs an exponential probability function to sample Hadamard patterns in a direction with high energy concentration of the Hadamard spectrum. We used the compressed-sensing algorithm for image reconstruction. The simulation and experimental results show that this sampling strategy can reconstruct object reliably and preserves the edge and details of images.
single-pixel imaging compressed sensing Hadamard matrix 
Chinese Optics Letters
2023, 21(7): 071101
作者单位
摘要
西安工业大学 电子信息工程学院,西安 710021
多输入多输出(Multiple-input-multiple-output,MIMO)可见光通信(Visible Light Communications,VLC)系统接收端需精确的信道状态信息用以解调信号,而常用的最小二乘算法对噪声敏感,估计误差较大,难以保证可靠性。基于信道稀疏特性,利用压缩感知方法进行MIMO-VLC信道估计,提出一种基于离散傅里叶变换(Discrete Fourier Transform,DFT)的稀疏度预测自适应匹配追踪(DFT Based Prediction-sparsity Adaptive Matching Pursuit,DFT-SAMP)算法。首先,通过DFT的稀疏度预测方法对信道冲激响应的稀疏度进行预估计,将估计的稀疏度作为算法初始步长,以快速逼近真实稀疏度,提高算法效率;其次,采用SAMP算法重构信道冲激响应,提高信道估计准确性,保证通信可靠性。基于2×2的MIMO-VLC系统信道估计实验结果表明,导频数为32时,本文算法相较于最小二乘算法在误码率满足前向纠错的误码率阈值(3.8×10-3)时所需的信噪比降低4.5 dB;利用DFT-SAMP算法进行信道估计,在保证可靠性的同时,运行效率相比SAMP算法提升约69%,为MIMO-VLC系统信道估计提供了更为有效的方式。
MIMO-VLC 压缩感知 信道估计 误码率 MIMO-VLC Compressed sensing Channel estimation Error rate 
光子学报
2023, 52(4): 0406002
Author Affiliations
Abstract
1 Department of Physics, Clarendon Laboratory, University of Oxford, Oxford, UK
2 Centre for Advanced Laser Applications, Ludwig-Maximilians-Universität München, Garching, Germany
3 John Adams Institute for Accelerator Science, Oxford, UK
Presented is a novel way to combine snapshot compressive imaging and lateral shearing interferometry in order to capture the spatio-spectral phase of an ultrashort laser pulse in a single shot. A deep unrolling algorithm is utilized for snapshot compressive imaging reconstruction due to its parameter efficiency and superior speed relative to other methods, potentially allowing for online reconstruction. The algorithm’s regularization term is represented using a neural network with 3D convolutional layers to exploit the spatio-spectral correlations that exist in laser wavefronts. Compressed sensing is not typically applied to modulated signals, but we demonstrate its success here. Furthermore, we train a neural network to predict the wavefronts from a lateral shearing interferogram in terms of Zernike polynomials, which again increases the speed of our technique without sacrificing fidelity. This method is supported with simulation-based results. While applied to the example of lateral shearing interferometry, the methods presented here are generally applicable to a wide range of signals, including Shack–Hartmann-type sensors. The results may be of interest beyond the context of laser wavefront characterization, including within quantitative phase imaging.
artificial neural networks compressed sensing high-power laser characterization wavefront measurement 
High Power Laser Science and Engineering
2023, 11(3): 03000e32
董旭 *
作者单位
摘要
宁波大学信息科学与工程学院,浙江 宁波 315211
在医疗诊断、目标预警、无损探伤等诸多民用和军用领域中,非接触的实时微波成像技术具有重要研究意义。基于逆散射成像理论,非迭代的反演思路具备天然的实时计算能力,但其成像结果粗糙难以实用。为了提高反演图像质量,提出一种基于稀疏感应电流的实时微波成像方法。该方法利用稀疏先验信息和压缩感知算法求解成像区域中的感应电流,并结合传统非迭代反演框架实现实时成像。全波仿真结果和微波成像系统实验验证了所提方法的有效性。相比于传统非迭代反演结果,所提方法在成像质量和成像速度方面有显著提高,在实时监测、快速成像等场合具有重要应用潜力。
成像系统 微波成像 压缩感知 感应电流 实时 imaging systems microwave imaging compressed sensing induced current real-time 
激光与光电子学进展
2023, 60(10): 1011006
作者单位
摘要
1 山东理工大学 电气与电子工程学院,山东 淄博 255049
2 潍坊工程职业学院,山东 潍坊 262500
集成成像技术作为一种重要的裸眼三维显示技术,在完整记录三维场景信息的同时,庞大的数据量给传输和存储带来了压力。为了实现图像的有效压缩和重构,根据光子计数集成成像的特点,基于分布式压缩感知理论,提出用于图像压缩与重构的方案。该方案将图像分为参考图像和非参考图像两类,对其设置不同的测量率并分别进行重构。为保证非参考图像的重构质量,提出一种联合重构算法。该算法首先对非参考图像进行分块测量,依据与参考图像之间的相关性进行图像块分类,然后结合参考图像测量值信息构建新的测量矢量,利用新的测量矢量完成初次图像重构。为了进一步提升图像重构质量,对初次重构结果进行二次残差补偿重构,获得最终重构结果。最后通过设置不同的测量率进行了大量实验,实验结果表明,所提算法在测量率为0.25时,图像重构质量可以达到30 dB,测量率为0.4时,图像质量可以达到35 dB,算法性能具有一定的优越性。
光子计数集成成像 图像压缩 图像重构 压缩感知 photon counting integral imaging image compression image reconstruction compressed sensing 
应用光学
2023, 44(2): 295
李虎 1,2,3刘雪峰 1,3姚旭日 4,5翟光杰 1,3
作者单位
摘要
1 中国科学院国家空间科学中心科学卫星运控部, 北京 100190
2 中国科学院国家空间科学中心复杂航天系统电子信息技术重点实验室, 北京 100190
3 中国科学院大学, 北京 100049
4 北京理工大学物理学院, 北京 100081
5 北京量子信息科学研究院, 北京 100193
计算层析成像光谱既有传统成像光谱仪获取目标二维空间和一维光谱“图谱合一”的能力, 还具有高通量测量和免扫描特性, 在光谱成像领域拥有广泛应用场景并得到大量研究。 根据中心切片定理, 计算层析成像光谱仪性能主要受焦平面阵列探测器(FPA)和二维色散元件的性能制约, 以往研究主要在改进二维色散元件设计以增加衍射级次和投影角度以提高精确重建光谱所需的采样量。 从FPA二维色散投影测量入手, 提出并行压缩感知理论和计算层析成像光谱结合的方法, 构建并行压缩感知计算层析成像光谱模型, 利用低分辨FPA实现更高分辨率的色散投影测量, 最终实现高于传统计算层析直接测量的性能水平。 该研究为验证该成像光谱模型的正确性与可行性, 先选用高光谱数据集对色散投影直接测量模型进行了三光谱立方体到二维色散投影和并行压缩感知测量模型重建的仿真实验, 在仿真结果正确的前提下使用连续谱激光器和反射式数字微镜进行了相应的光学系统实验, 完成了投影矩阵的逐点精确标定, 并提出提高标定效率的并行标定方法, 将标定时间降低到单点标定的四分之一。 结果显示并行压缩感知计算层析成像光谱可以获得更高的光谱重建质量, 能获得高于FPA自身性能的高分辨光谱投影并大幅提高光谱重建质量, 验证了所提并行压缩感知计算层析成像光谱的正确性与可行性。
计算层析成像光谱 分辨率 压缩感知 并行压缩感知 Computed-tomography imaging spectrometry Resolution Compressed sensing Block compressed sensing 
光谱学与光谱分析
2023, 43(2): 348

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