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单像素压缩成像高质量图像重建特征函数

光学学报 2024年第7期44卷 61-73页

作者：居世昌蔡俊杰龚文林苏州大学光电科学与工程学院江苏苏州215006

通过测量矩阵获取Gram矩阵,梳理了Gram矩阵与系统点扩散函数的关系,进而基于点扩散函数提出最强旁瓣峰值大小、叠加旁瓣峰值大小、空间距离和频谱余弦相似度4个特征参量。在此基础上,构建了一种单像素压缩成像高质量图像重建的特征函数... 详细信息

通过测量矩阵获取Gram矩阵,梳理了Gram矩阵与系统点扩散函数的关系,进而基于点扩散函数提出最强旁瓣峰值大小、叠加旁瓣峰值大小、空间距离和频谱余弦相似度4个特征参量。在此基础上,构建了一种单像素压缩成像高质量图像重建的特征函数,建立了可重建的目标稀疏度与特征函数的关系,并通过数值模拟和实验验证了所提特征函数的有效性,该工作对于单像素成像系统测量矩阵的优化设计具有重要借鉴意义。

关键词：成像系统单像素成像压缩感知测量矩阵特征函数

Far-field super-resolution ghost imaging with a deep neural network constraint

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Light(Science & Applications) 2022年第1期11卷 27-37页

作者： Fei Wang Chenglong Wang Mingliang Chen wenlin gong Yu Zhang Shensheng Han Guohai Situ Shanghai Institute of Optics and Fine Mechanics Chinese Academy of SciencesShanghai 201800China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhou 310024China CAS Center for Excellence in Ultra-intense Laser Science Shanghai 201800China

Ghost imaging(GI)facilitates image acquisition under low-light conditions by single-pixel measurements and thus has great potential in applications in various fields ranging from biomedical imaging to remote ***,GI usually requires a large amount of single-pixel samplings in order to reconstruct a high-resolution image,imposing a practical limit for its *** we propose a far-field super-resolution GI technique that incorporates the physical model for GI image formation into a deep neural *** resulting hybrid neural network does not need to pre-train on any dataset,and allows the reconstruction of a far-field image with the resolution beyond the diffraction ***,the physical model imposes a constraint to the network output,making it effectively *** experimentally demonstrate the proposed GI technique by imaging a flying drone,and show that it outperforms some other widespread GI techniques in terms of both spatial resolution and sampling *** believe that this study provides a new framework for GI,and paves a way for its practical applications.

关键词： neural ghost Ghost

Performance analysis of ghost imaging lidar in background light environment

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Photonics Research 2017年第5期5卷 431-435页

作者： CHENJIN DENG LONG PAN CHENGLONG WANG XIN GAO wenlin gong SHENSHENG HAN Key Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS Shanghai Institute of Optics and Fine MechanicsChinese Academy of Sciences University of Chinese Academy of Sciences

The effect of background light on the imaging quality of three typical ghost imaging(GI) lidar systems(namely narrow pulsed GI lidar, heterodyne GI lidar, and pulse-compression GI lidar via coherent detection) is investigated. By computing the signal-to-noise ratio(SNR) of fluctuation-correlation GI, our analytical results, which are backed up by numerical simulations, demonstrate that pulse-compression GI lidar via coherent detection has the strongest capacity against background light, whereas the reconstruction quality of narrow pulsed GI lidar is the most vulnerable to background light. The relationship between the peak SNR of the reconstruction image andσ(namely, the signal power to background power ratio) for the three GI lidar systems is also presented, and theresults accord with the curve of SNR-σ.

关键词： GI SNR Performance analysis of ghost imaging lidar in background light environment

Super-resolution imaging via sparsity constraint and sparse speckle illumination

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Chinese Physics B 2018年第7期27卷 325-330页

作者： Pengwei Wang Wei Li Chenglong Wang Zunwang Bo wenlin gong Key Laboratory for Quantum Optics and Center for Cold Atom Physics Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai 201800 China University of Chinese Academy of Sciences Beijing 100049 China Academy of Opto-electronics Chinese Academy of Sciences Beijing 100094 China

We present an imaging approach via sparsity constraint and sparse speckle illumination which can dramatically en- hance the optical system＇s imaging resolution. When the object is illuminated by some sparse speckles and the sparse reconstruction algorithm is utilized to restore the blur image, numerical simulated results demonstrate that the image, whose resolution exceeds the Rayleigh limit, can be stably reconstructed even if the detection signal-to-noise ratio （SNR） is less than 10 dB. Factors affecting the quality of the reconstructed image, such as the coded pattern＇s sparsity and the detection SNR, are also studied,

关键词： imaging and optical processing

High-resolution pseudo-inverse ghost imaging

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Photonics Research 2015年第5期3卷 234-237页

作者： wenlin gong Key Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences

We present a pseudo-inverse ghost imaging(PGI) technique which can dramatically enhance the spatial transverse resolution of pseudo-thermal ghost imaging(GI). In comparison with conventional GI, PGI can break the limitation on the imaging resolution imposed by the speckle’s transverse size on the object plane and also enables the reconstruction of an N-pixel image from much less than N measurements. This feature also allows high-resolution imaging of gray-scale objects. Experimental and numerical data assessing the performance of the technique are presented.

关键词： PGI PSNR High-resolution pseudo-inverse ghost imaging

A FAST CONVERGING SPARSE RECONSTRUCTION ALGORITHM IN GHOST IMAGING

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Journal of Electronics(China) 2012年第6期29卷 617-620页

作者： Li Enrong Chen Mingliang gong wenlin Wang Hui Han Shensheng Key Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS Shanghai Institute of Optics and Fine MechanicsChinese Academy of Sciences

A fast converging sparse reconstruction algorithm in ghost imaging is presented. It utilizes total variation regularization and its formulation is based on the Karush-Kuhn-Tucker (KKT) theorem in the theory of convex optimization. Tests using experimental data show that, compared with the algorithm of Gradient Projection for Sparse Reconstruction (GPSR), the proposed algorithm yields better results with less computation work.

关键词： Compressive sensing Ghost Imaging (GI) Sparse reconstruction Karush-Kuhn-Tucker (KKT) condition Gradient projection

Performance comparison of ghost imaging versus conventional imaging in photon shot noise cases

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Chinese Optics Letters 2020年第7期18卷 40-44页

作者： Zijie Li Qing Zhao wenlin gong Center for Quantum Technology Research School of PhysicsBeijing Institute of TechnologyBeijing 100081China Key Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS Shanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China

The performances of ghost imaging and conventional imaging in photon shot noise cases are investigated. We define an imaging signal-to-noise ratio called SNRtranwhere only the object’s transmission region is used to evaluate the imaging quality and it can be applied to ghost imaging(GI) with any random pattern. Both the values SNRtran GIof GI and SNRtran CIof conventional imaging in photon shot noise cases are deduced from a simple statistical analysis. The analytical results, which are backed up by numerical simulations, demonstrate that the value SNRtran GIis related to the ratio between the object’s transmission area Aoand the number density of photons illuminating the object plane Io, which is similar to the theoretical results based on the first principle of GI with a Gaussian speckle field deduced by B. I. Erkmen and J. H. Shapiro [in Adv. Opt. Photonics 2, 405–450(2010)]. In addition, we also show that the value SNRtran CIwill be larger than SNRtran GIwhen Ao is beyond a threshold value.

关键词： ghost imaging photon shot noise signal-to-noise ratio speckle

Ghost imaging for an axially moving target with an unknown constant speed

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Photonics Research 2015年第4期3卷 153-157页

作者： Xiaohui Li Chenjin Deng Mingliang Chen wenlin gong Shensheng Han Key Laboratory for Quantum Optics and Center for Cold Atom Physics Shanghai Institute of Optics and Fine MechanicsChinese Academy of Sciences

The influence of the axial relative motion between the target and the source on ghost imaging(GI) is *** the analytical and experimental results show that the transverse resolution of GI is reduced as the deviation of the target’s center position from the optical axis or the axial motion range increases. To overcome the motion blur,we propose a deblurring method based on speckle-resizing and speed retrieval, and we experimentally validate its effectiveness for an axially moving target with an unknown constant speed. The results demonstrated here will be very useful to forward-looking GI remote sensing.

关键词： GI Ghost imaging for an axially moving target with an unknown constant speed

Scalar-matrix-structured ghost imaging

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Photonics Research 2016年第6期4卷 281-285页

作者： Chao Yang Chenglong Wang Jian Guan Chi Zhang Shuxu Guo wenlin gong Fengli Gao State Key Laboratory on Integrated Optoelectronics College of Electronic Science and Engineering Jilin University Key Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences

The features of the characteristic matrix used in linear intensity correlation reconstruction methods are directly related to the quality of ghost imaging. In order to suppress the noise caused by the off-diagonal elements in the characteristic matrix, we propose a reconstruction method for ghost imaging called scalar-matrix-structured ghost imaging(SMGI). The characteristic matrix is made to approximate a scalar matrix by modifying the measurement matrix. Experimental results show that SMGI improves the peak signal-to-noise ratio of the object reconstruction significantly compared with differential ghost imaging, even in the case of a nonzero two-arm longitudinal difference, which is a promising result for practical applications.

关键词： DGI Scalar-matrix-structured ghost imaging