The influence of the axial relative motion between the target and the source on ghost imaging(GI) is investigated.Both the analytical and experimental results show that the transverse resolution of GI is reduced as th...The influence of the axial relative motion between the target and the source on ghost imaging(GI) is investigated.Both 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.展开更多
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 sensing.H...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 sensing.However,GI usually requires a large amount of single-pixel samplings in order to reconstruct a high-resolution image,imposing a practical limit for its applications.Here we propose a far-field super-resolution GI technique that incorporates the physical model for GI image formation into a deep neural network.The 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 limit.Furthermore,the physical model imposes a constraint to the network output,making it effectively interpretable.We 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 ratio.We believe that this study provides a new framework for GI,and paves a way for its practical applications.展开更多
We present a series of results acquired at a 2-kilometer distance using our lidar system under several weather conditions, clear, cloudy, light rain, moderately foggy, and night. The experimental results show that gho...We present a series of results acquired at a 2-kilometer distance using our lidar system under several weather conditions, clear, cloudy, light rain, moderately foggy, and night. The experimental results show that ghost imaging lidar via spar-sity constraints can realize imaging in all these weather conditions.展开更多
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 inve...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.展开更多
The optical memory effect is an interesting phenomenon that has attracted considerable attention in recent decades. Here, we present a new physical picture of the optical memory effect, in which the memory effect and ...The optical memory effect is an interesting phenomenon that has attracted considerable attention in recent decades. Here, we present a new physical picture of the optical memory effect, in which the memory effect and the conventional spatial shift invariance are united. Based on this picture we depict the role of thickness, scattering times, and anisotropy factor and derive equations to calculate the ranges of the angular memory effect(AME) of different scattering components(ballistic light, singly scattered, doubly scattered, etc.), and hence a more accurate equation for the real AME ranges of volumetric turbid media. A conventional random phase mask model is modified according to the new picture. The self-consistency of the simulation model and its agreement with the experiment demonstrate the rationality of the model and the physical picture, which provide powerful tools for more sophisticated studies of the memory-effect-related phenomena and wavefront-sensitive techniques, such as wavefront shaping, optical phase conjugation, and optical trapping in/through scattering media.展开更多
The goals of B2B electronic commerce and supply chain management system are to implement interoperability of independent enterprises, to smooth the information flow between them and to deploy business processes over m...The goals of B2B electronic commerce and supply chain management system are to implement interoperability of independent enterprises, to smooth the information flow between them and to deploy business processes over multiple enterprises. The inherent characteristics of workflow system make it suitable to implement the cross organization management. This paper, firstly, proposes an inter enterprises workflow model based on the agreement to support the construction of supply chain management system and B2B electronic commerce. This model has extended the standard workflow model. After that, an architecture which supports the model has been introduced, especially it details the structure and implementation of interfaces between enterprises.展开更多
Single-pixel imaging(SPI) is a typical computational imaging modality that allows two-and three-dimensional image reconstruction from a one-dimensional bucket signal acquired under structured illumination.It is in par...Single-pixel imaging(SPI) is a typical computational imaging modality that allows two-and three-dimensional image reconstruction from a one-dimensional bucket signal acquired under structured illumination.It is in particular of interest for imaging under low light conditions and in spectral regions where good cameras are unavailable.However,the resolution of the reconstructed image in SPI is strongly dependent on the number of measurements in the temporal domain.Data-driven deep learning has been proposed for high-quality image reconstruction from a undersampled bucket signal.But the generalization issue prohibits its practical application.Here we propose a physics-enhanced deep learning approach for SPI.By blending a physics-informed layer and a model-driven fine-tuning process,we show that the proposed approach is generalizable for image reconstruction.We implement the proposed method in an in-house SPI system and an outdoor single-pixel LiDAR system,and demonstrate that it outperforms some other widespread SPI algorithms in terms of both robustness and fidelity.The proposed method establishes a bridge between data-driven and model-driven algorithms,allowing one to impose both data and physics priors for inverse problem solvers in computational imaging,ranging from remote sensing to microscopy.展开更多
Quantum detection technology and quantum imaging based on two-photon interference effects, along with various new conceptual imaging schemes inspired by the two-photon interference quantum imaging, have significantly ...Quantum detection technology and quantum imaging based on two-photon interference effects, along with various new conceptual imaging schemes inspired by the two-photon interference quantum imaging, have significantly redefined the sight and content of imaging technology. This has rejuvenated the ancient discipline of imaging science, transforming it into a burgeoning field at the intersection of statistical and quantum optics, information science, applied mathematics, artificial intelligence, computer vision, light field manipulation technology, and compressive sensing technology. These advancements provide practical and innovative technological approaches to greatly enhance the capability and efficiency of image information acquisition in various application scenarios.Profs.展开更多
Ghost imaging(GI)can nonlocally image objects by exploiting the fluctuation characteristics of light fields,where the spatial resolution is determined by the normalized second-order correlation function g^(2) .However...Ghost imaging(GI)can nonlocally image objects by exploiting the fluctuation characteristics of light fields,where the spatial resolution is determined by the normalized second-order correlation function g^(2) .However,the spatial shift-invariant property of g^(2) is distorted when the number of samples is limited,which hinders the deconvolution methods from improving the spatial resolution of GI.In this paper,based on prior imaging systems,we propose a preconditioned deconvolution method to improve the imaging resolution of GI by refining the mutual coherence of a sampling matrix in GI.Our theoretical analysis shows that the preconditioned deconvolution method actually extends the deconvolution technique to GI and regresses into the classical deconvolution technique for the conventional imaging system.The imaging resolution of GI after preconditioning is restricted to the detection noise.Both simulation and experimental results show that the spatial resolution of the reconstructed image is obviously enhanced by using the preconditioned deconvolution method.In the experiment,1.4-fold resolution enhancement over Rayleigh criterion is achieved via the preconditioned deconvolution.Our results extend the deconvolution technique that is only applicable to spatial shift-invariant imaging systems to all linear imaging systems,and will promote their applications in biological imaging and remote sensing for high-resolution imaging demands.展开更多
Imaging through scattering media is valuable for many areas,such as biomedicine and communication.Recent progress enabled by deep learning(DL)has shown superiority especially in the model generalization.However,there ...Imaging through scattering media is valuable for many areas,such as biomedicine and communication.Recent progress enabled by deep learning(DL)has shown superiority especially in the model generalization.However,there is a lack of research to physically reveal the origin or define the boundary for such model scalability,which is important for utilizing DL approaches for scalable imaging despite scattering with high confidence.In this paper,we find the amount of the ballistic light component in the output field is the prerequisite for endowing a DL model with generalization capability by using a“one-to-all”training strategy,which offers a physical meaning invariance among the multisource data.The findings are supported by both experimental and simulated tests in which the roles of scattered and ballistic components are revealed in contributing to the origin and physical boundary of the model scalability.Experimentally,the generalization performance of the network is enhanced by increasing the portion of ballistic photons in detection.The mechanism understanding and practical guidance by our research are beneficial for developing DL methods for descattering with high adaptivity.展开更多
An integrated enterprise workflow model called PPROCE is presented firstly. Then, an enterprise’s ontology established by TOVE and Process Specification Language (PSL) is studied. Combined with TOVE’s partition idea...An integrated enterprise workflow model called PPROCE is presented firstly. Then, an enterprise’s ontology established by TOVE and Process Specification Language (PSL) is studied. Combined with TOVE’s partition idea, PSL is extended and new PSL Extensions is created to define the ontology of process, organization, resource and product in the PPROCE model. As a result, PPROCE model can be defined by a set of corresponding formal language. It facilitates the future work not only in the model verification, model optimization and model simulation, but also in the model translation.展开更多
We propose a plug-and-play(Pn P) method that uses deep-learning-based denoisers as regularization priors for spectral snapshot compressive imaging(SCI). Our method is efficient in terms of reconstruction quality and s...We propose a plug-and-play(Pn P) method that uses deep-learning-based denoisers as regularization priors for spectral snapshot compressive imaging(SCI). Our method is efficient in terms of reconstruction quality and speed trade-off, and flexible enough to be ready to use for different compressive coding mechanisms. We demonstrate the efficiency and flexibility in both simulations and five different spectral SCI systems and show that the proposed deep Pn P prior could achieve state-of-the-art results with a simple plug-in based on the optimization framework. This paves the way for capturing and recovering multi-or hyperspectral information in one snapshot,which might inspire intriguing applications in remote sensing, biomedical science, and material science. Our code is available at: https://github.com/zsm1211/Pn P-CASSI.展开更多
High resolution imaging is achieved using increasingly larger apertures and successively shorter wavelengths.Optical aperture synthesis is an important high-resolution imaging technology used in astronomy.Conventional...High resolution imaging is achieved using increasingly larger apertures and successively shorter wavelengths.Optical aperture synthesis is an important high-resolution imaging technology used in astronomy.Conventional long baseline amplitude interferometry is susceptible to uncontrollable phase fluctuations,and the technical difficulty increases rapidly as the wavelength decreases.The intensity interferometry inspired by HBT experiment is essentially insensitive to phase fluctuations,but suffers from a narrow spectral bandwidth which results in a lack of effective photons.In this study,we propose optical synthetic aperture imaging based on spatial intensity interferometry.This not only realizes diffraction-limited optical aperture synthesis in a single shot,but also enables imaging with a wide spectral bandwidth,which greatly improves the optical energy efficiency of intensity interferometry.And this method is insensitive to the optical path difference between the sub-apertures.Simulations and experiments present optical aperture synthesis diffraction-limited imaging through spatial intensity interferometry in a 100 nm spectral width of visible light,whose maximum optical path difference between the sub-apertures reaches 69λ.This technique is expected to provide a solution for optical aperture synthesis over kilometer-long baselines at optical wavelengths.展开更多
Different from X-rays,neutrons mainly interact with atomic nuclei and magnetic moments in materials.This makes neutron imaging a complementary contrast mechanism to X-ray imaging.Neutron imaging aims to infer the inte...Different from X-rays,neutrons mainly interact with atomic nuclei and magnetic moments in materials.This makes neutron imaging a complementary contrast mechanism to X-ray imaging.Neutron imaging aims to infer the internal material information of the object by measuring the changes in neutron beam parameters,such as the intensity attenuation,polarization,scattering,and matter wave interference.It has a wide range of applications in industry such as the inspection of batteries,magnetic structure analysis,and strain mapping in alloys.展开更多
This paper presents a novel ontology mapping approach based on rough set theory and instance selection.In this appoach the construction approach of a rough set-based inference instance base in which the instance selec...This paper presents a novel ontology mapping approach based on rough set theory and instance selection.In this appoach the construction approach of a rough set-based inference instance base in which the instance selection(involving similarity distance,clustering set and redundancy degree)and discernibility matrix-based feature reduction are introduced respectively;and an ontology mapping approach based on multi-dimensional attribute value joint distribution is proposed.The core of this mapping aI overlapping of the inference instance space.Only valuable instances and important attributes can be selected into the ontology mapping based on the multi-dimensional attribute value joint distribution,so the sequently mapping efficiency is improved.The time complexity of the discernibility matrix-based method and the accuracy of the mapping approach are evaluated by an application example and a series of analyses and comparisons.展开更多
High-resolution optical imaging through or within thick scattering media is a long sought after yet unreached goal.In the past decade,the thriving technique developments in wavefront measurement and manipulation do no...High-resolution optical imaging through or within thick scattering media is a long sought after yet unreached goal.In the past decade,the thriving technique developments in wavefront measurement and manipulation do not significantly push the boundary forward.The optical diffusion limit is still a ceiling.In this work,we propose that a scattering medium can be conceptualized as an assembly of randomly packed pinhole cameras and the corresponding speckle pattern as a superposition of randomly shifted pinhole images.The concept is demonstrated through both simulation and experiments,confirming the new perspective to interpret the mechanism of information transmission through scattering media under incoherent illumination.We also analyze the efficiency of single-pinhole and dual-pinhole channels.While in infancy,the proposed method reveals a new perspective to understand imaging and information transmission through scattering media.展开更多
The point-spread function of an optical system determines its optical resolution for both spatial and temporal imaging. For spatial imaging, it is given by a Fourier transform of the pupil function of the system. For ...The point-spread function of an optical system determines its optical resolution for both spatial and temporal imaging. For spatial imaging, it is given by a Fourier transform of the pupil function of the system. For temporal imaging based on nonlinear optical processes, such as sum-frequency generation or four-wave mixing, the pointspread function is related to the waveform of the pump wave by a nonlinear transformation. We compare the point-spread functions of three temporal imaging schemes： sum-frequency generation, co-propagating four-wave mixing, and counter-propagating four-wave mixing, and demonstrate that the last scheme provides the best temporal resolution. Our results are valid for both quantum and classical temporal imaging.展开更多
At present,reconstruction of megapixel and high-fidelity images with few measurements is a major challenge for X-ray ghost imaging(XGI).The available strategies require massive measurements and reconstruct low-fidelit...At present,reconstruction of megapixel and high-fidelity images with few measurements is a major challenge for X-ray ghost imaging(XGI).The available strategies require massive measurements and reconstruct low-fidelity images of less than 300 × 300 pixels.Inspired by the concept of synthetic aperture radar,synthetic aperture XGI(SAXGI)integrated with compressive sensing is proposed to solve this problem with a binned detector in the object arm.Experimental results demonstrated that SAXGI can accurately reconstruct the 1200 × 1200 pixels image of a binary sample of tangled strands of tungsten fiber from 660 measurements.Accordingly,SAXGI is a promising solution for the practical application of XGI.展开更多
This paper proposes a constructive approach to solving geometric constraint systems.The approach incorporates graph-based and rule-based approaches, and achieves interactive speed.The paper presents a graph representa...This paper proposes a constructive approach to solving geometric constraint systems.The approach incorporates graph-based and rule-based approaches, and achieves interactive speed.The paper presents a graph representation of geometric conStraint syStems, and discusses in detailthe algorithm of geometric reasoning based on poinl-cluster reduction. An example is made forillustration.展开更多
We investigate the influence of the source’s energy fluctuation on both computational ghost imaging and computational ghost imaging via sparsity constraint,and if the reconstruction quality will decrease with the inc...We investigate the influence of the source’s energy fluctuation on both computational ghost imaging and computational ghost imaging via sparsity constraint,and if the reconstruction quality will decrease with the increase of the source’s energy fluctuation.In order to overcome the problem of image degradation,a correction approach against the source’s energy fluctuation is proposed by recording the source’s fluctuation with a monitor before modulation and correcting the echo signal or the intensity of computed reference light field with the data recorded by the monitor.Both the numerical simulation and experimental results demonstrate that computational ghost imaging via sparsity constraint can be enhanced by correcting the echo signal or the intensity of computed reference light field,while only correcting the echo signal is valid for computational ghost imaging.展开更多
基金supported by the Hi-Tech Research and Development Program of China under Grant Project No. 2013AA122901
文摘The influence of the axial relative motion between the target and the source on ghost imaging(GI) is investigated.Both 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.
基金the National Natural Science Foundation of China(61991452,62061136005)the Key Research Program of Frontier Sciences of the Chinese Academy of Sciences(QYZDB-SSW-JSC002)the Sino-German Center(GZ1391).
文摘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 sensing.However,GI usually requires a large amount of single-pixel samplings in order to reconstruct a high-resolution image,imposing a practical limit for its applications.Here we propose a far-field super-resolution GI technique that incorporates the physical model for GI image formation into a deep neural network.The 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 limit.Furthermore,the physical model imposes a constraint to the network output,making it effectively interpretable.We 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 ratio.We believe that this study provides a new framework for GI,and paves a way for its practical applications.
文摘We present a series of results acquired at a 2-kilometer distance using our lidar system under several weather conditions, clear, cloudy, light rain, moderately foggy, and night. The experimental results show that ghost imaging lidar via spar-sity constraints can realize imaging in all these weather conditions.
基金National Natural Science Foundation of China(NSFC)(61571427)Ministry of Science and Technology of the People’s Republic of China(MOST)(2013AA122901)Youth Innovation Promotion Association of the Chinese Academy of Sciences(2013162)
文摘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.
基金National Key Research and Development Program of China Stem Cell and Translational Research(2016YFC0100602)
文摘The optical memory effect is an interesting phenomenon that has attracted considerable attention in recent decades. Here, we present a new physical picture of the optical memory effect, in which the memory effect and the conventional spatial shift invariance are united. Based on this picture we depict the role of thickness, scattering times, and anisotropy factor and derive equations to calculate the ranges of the angular memory effect(AME) of different scattering components(ballistic light, singly scattered, doubly scattered, etc.), and hence a more accurate equation for the real AME ranges of volumetric turbid media. A conventional random phase mask model is modified according to the new picture. The self-consistency of the simulation model and its agreement with the experiment demonstrate the rationality of the model and the physical picture, which provide powerful tools for more sophisticated studies of the memory-effect-related phenomena and wavefront-sensitive techniques, such as wavefront shaping, optical phase conjugation, and optical trapping in/through scattering media.
文摘The goals of B2B electronic commerce and supply chain management system are to implement interoperability of independent enterprises, to smooth the information flow between them and to deploy business processes over multiple enterprises. The inherent characteristics of workflow system make it suitable to implement the cross organization management. This paper, firstly, proposes an inter enterprises workflow model based on the agreement to support the construction of supply chain management system and B2B electronic commerce. This model has extended the standard workflow model. After that, an architecture which supports the model has been introduced, especially it details the structure and implementation of interfaces between enterprises.
基金National Natural Science Foundation of China(61991452, 62061136005)Key Research Program of Frontier Sciences of the Chinese Academy of Sciences(QYZDB-SSW-JSC002)Chinesisch-Deutsche Zentrum für Wissenschaftsf?rderung (GZ1391)。
文摘Single-pixel imaging(SPI) is a typical computational imaging modality that allows two-and three-dimensional image reconstruction from a one-dimensional bucket signal acquired under structured illumination.It is in particular of interest for imaging under low light conditions and in spectral regions where good cameras are unavailable.However,the resolution of the reconstructed image in SPI is strongly dependent on the number of measurements in the temporal domain.Data-driven deep learning has been proposed for high-quality image reconstruction from a undersampled bucket signal.But the generalization issue prohibits its practical application.Here we propose a physics-enhanced deep learning approach for SPI.By blending a physics-informed layer and a model-driven fine-tuning process,we show that the proposed approach is generalizable for image reconstruction.We implement the proposed method in an in-house SPI system and an outdoor single-pixel LiDAR system,and demonstrate that it outperforms some other widespread SPI algorithms in terms of both robustness and fidelity.The proposed method establishes a bridge between data-driven and model-driven algorithms,allowing one to impose both data and physics priors for inverse problem solvers in computational imaging,ranging from remote sensing to microscopy.
文摘Quantum detection technology and quantum imaging based on two-photon interference effects, along with various new conceptual imaging schemes inspired by the two-photon interference quantum imaging, have significantly redefined the sight and content of imaging technology. This has rejuvenated the ancient discipline of imaging science, transforming it into a burgeoning field at the intersection of statistical and quantum optics, information science, applied mathematics, artificial intelligence, computer vision, light field manipulation technology, and compressive sensing technology. These advancements provide practical and innovative technological approaches to greatly enhance the capability and efficiency of image information acquisition in various application scenarios.Profs.
基金National Key Research and Development Program of China(2017YFB0503303)National Natural Science Foundation of China(61991454,11627811,61971146)+1 种基金Shanghai Municipal Science and Technology Major Project(2018SHZDZX01)Open Project of Chinese Academy of Sciences.
文摘Ghost imaging(GI)can nonlocally image objects by exploiting the fluctuation characteristics of light fields,where the spatial resolution is determined by the normalized second-order correlation function g^(2) .However,the spatial shift-invariant property of g^(2) is distorted when the number of samples is limited,which hinders the deconvolution methods from improving the spatial resolution of GI.In this paper,based on prior imaging systems,we propose a preconditioned deconvolution method to improve the imaging resolution of GI by refining the mutual coherence of a sampling matrix in GI.Our theoretical analysis shows that the preconditioned deconvolution method actually extends the deconvolution technique to GI and regresses into the classical deconvolution technique for the conventional imaging system.The imaging resolution of GI after preconditioning is restricted to the detection noise.Both simulation and experimental results show that the spatial resolution of the reconstructed image is obviously enhanced by using the preconditioned deconvolution method.In the experiment,1.4-fold resolution enhancement over Rayleigh criterion is achieved via the preconditioned deconvolution.Our results extend the deconvolution technique that is only applicable to spatial shift-invariant imaging systems to all linear imaging systems,and will promote their applications in biological imaging and remote sensing for high-resolution imaging demands.
基金National Natural Science Foundation of China(81930048)Guangdong Science and Technology Department(2019BT02X105)+2 种基金Research Grants Council,University Grants Committee(15217721,C7074-21GF,R5029-19)Innovation and Technology Commission(GHP/043/19SZ,GHP/044/19GD)Hong Kong Polytechnic University(P0038180,P0039517,P0043485)。
文摘Imaging through scattering media is valuable for many areas,such as biomedicine and communication.Recent progress enabled by deep learning(DL)has shown superiority especially in the model generalization.However,there is a lack of research to physically reveal the origin or define the boundary for such model scalability,which is important for utilizing DL approaches for scalable imaging despite scattering with high confidence.In this paper,we find the amount of the ballistic light component in the output field is the prerequisite for endowing a DL model with generalization capability by using a“one-to-all”training strategy,which offers a physical meaning invariance among the multisource data.The findings are supported by both experimental and simulated tests in which the roles of scattered and ballistic components are revealed in contributing to the origin and physical boundary of the model scalability.Experimentally,the generalization performance of the network is enhanced by increasing the portion of ballistic photons in detection.The mechanism understanding and practical guidance by our research are beneficial for developing DL methods for descattering with high adaptivity.
文摘An integrated enterprise workflow model called PPROCE is presented firstly. Then, an enterprise’s ontology established by TOVE and Process Specification Language (PSL) is studied. Combined with TOVE’s partition idea, PSL is extended and new PSL Extensions is created to define the ontology of process, organization, resource and product in the PPROCE model. As a result, PPROCE model can be defined by a set of corresponding formal language. It facilitates the future work not only in the model verification, model optimization and model simulation, but also in the model translation.
文摘We propose a plug-and-play(Pn P) method that uses deep-learning-based denoisers as regularization priors for spectral snapshot compressive imaging(SCI). Our method is efficient in terms of reconstruction quality and speed trade-off, and flexible enough to be ready to use for different compressive coding mechanisms. We demonstrate the efficiency and flexibility in both simulations and five different spectral SCI systems and show that the proposed deep Pn P prior could achieve state-of-the-art results with a simple plug-in based on the optimization framework. This paves the way for capturing and recovering multi-or hyperspectral information in one snapshot,which might inspire intriguing applications in remote sensing, biomedical science, and material science. Our code is available at: https://github.com/zsm1211/Pn P-CASSI.
基金supported by National Natural Foundation of China(Grant No.61991454)the project of CAS Interdisciplinary Innovation Team。
文摘High resolution imaging is achieved using increasingly larger apertures and successively shorter wavelengths.Optical aperture synthesis is an important high-resolution imaging technology used in astronomy.Conventional long baseline amplitude interferometry is susceptible to uncontrollable phase fluctuations,and the technical difficulty increases rapidly as the wavelength decreases.The intensity interferometry inspired by HBT experiment is essentially insensitive to phase fluctuations,but suffers from a narrow spectral bandwidth which results in a lack of effective photons.In this study,we propose optical synthetic aperture imaging based on spatial intensity interferometry.This not only realizes diffraction-limited optical aperture synthesis in a single shot,but also enables imaging with a wide spectral bandwidth,which greatly improves the optical energy efficiency of intensity interferometry.And this method is insensitive to the optical path difference between the sub-apertures.Simulations and experiments present optical aperture synthesis diffraction-limited imaging through spatial intensity interferometry in a 100 nm spectral width of visible light,whose maximum optical path difference between the sub-apertures reaches 69λ.This technique is expected to provide a solution for optical aperture synthesis over kilometer-long baselines at optical wavelengths.
文摘Different from X-rays,neutrons mainly interact with atomic nuclei and magnetic moments in materials.This makes neutron imaging a complementary contrast mechanism to X-ray imaging.Neutron imaging aims to infer the internal material information of the object by measuring the changes in neutron beam parameters,such as the intensity attenuation,polarization,scattering,and matter wave interference.It has a wide range of applications in industry such as the inspection of batteries,magnetic structure analysis,and strain mapping in alloys.
基金the National High Technology Research and Development Program of China(No.2002AA411420)the National Key Basic Research and Development Program of China(No.2003CB316905)the National Natural Science Foundation of China(No.60374071)
文摘This paper presents a novel ontology mapping approach based on rough set theory and instance selection.In this appoach the construction approach of a rough set-based inference instance base in which the instance selection(involving similarity distance,clustering set and redundancy degree)and discernibility matrix-based feature reduction are introduced respectively;and an ontology mapping approach based on multi-dimensional attribute value joint distribution is proposed.The core of this mapping aI overlapping of the inference instance space.Only valuable instances and important attributes can be selected into the ontology mapping based on the multi-dimensional attribute value joint distribution,so the sequently mapping efficiency is improved.The time complexity of the discernibility matrix-based method and the accuracy of the mapping approach are evaluated by an application example and a series of analyses and comparisons.
基金supported by the National Key Research and Development Program of China(Grant No.2016YFC0100602)National Natural Science Foundation of China(Grant Nos.81930048,81671726,and 81627805)+2 种基金Guangdong Science and Technology Commission(Grant Nos.2019BT02X105,and 2019A1515011374)Hong Kong Research Grant Council(Grant Nos.15217721,R5029-19,and C7074-21GF)Hong Kong Innovation and Technology Commission(Grant Nos.GHP/043/19SZ and GHP/044/19GD).
文摘High-resolution optical imaging through or within thick scattering media is a long sought after yet unreached goal.In the past decade,the thriving technique developments in wavefront measurement and manipulation do not significantly push the boundary forward.The optical diffusion limit is still a ceiling.In this work,we propose that a scattering medium can be conceptualized as an assembly of randomly packed pinhole cameras and the corresponding speckle pattern as a superposition of randomly shifted pinhole images.The concept is demonstrated through both simulation and experiments,confirming the new perspective to interpret the mechanism of information transmission through scattering media under incoherent illumination.We also analyze the efficiency of single-pinhole and dual-pinhole channels.While in infancy,the proposed method reveals a new perspective to understand imaging and information transmission through scattering media.
基金support by the Hi-Tech Research and Development Program of China(Nos.2013AA122902 and 2013AA122901)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB21030200)
文摘The point-spread function of an optical system determines its optical resolution for both spatial and temporal imaging. For spatial imaging, it is given by a Fourier transform of the pupil function of the system. For temporal imaging based on nonlinear optical processes, such as sum-frequency generation or four-wave mixing, the pointspread function is related to the waveform of the pump wave by a nonlinear transformation. We compare the point-spread functions of three temporal imaging schemes： sum-frequency generation, co-propagating four-wave mixing, and counter-propagating four-wave mixing, and demonstrate that the last scheme provides the best temporal resolution. Our results are valid for both quantum and classical temporal imaging.
基金This work was supported by the National Key Research and Development Program of China(Nos.2017YFA0206004,2017YFA0206002,2018YFC0206002,and 2017YFA0403801)the National Natural Science Foundation of China(NSFC)(No.81430087).
文摘At present,reconstruction of megapixel and high-fidelity images with few measurements is a major challenge for X-ray ghost imaging(XGI).The available strategies require massive measurements and reconstruct low-fidelity images of less than 300 × 300 pixels.Inspired by the concept of synthetic aperture radar,synthetic aperture XGI(SAXGI)integrated with compressive sensing is proposed to solve this problem with a binned detector in the object arm.Experimental results demonstrated that SAXGI can accurately reconstruct the 1200 × 1200 pixels image of a binary sample of tangled strands of tungsten fiber from 660 measurements.Accordingly,SAXGI is a promising solution for the practical application of XGI.
文摘This paper proposes a constructive approach to solving geometric constraint systems.The approach incorporates graph-based and rule-based approaches, and achieves interactive speed.The paper presents a graph representation of geometric conStraint syStems, and discusses in detailthe algorithm of geometric reasoning based on poinl-cluster reduction. An example is made forillustration.
基金supported by the Youth Innovation Promotion Association of the Chinese Academy of Sciences,the Defense Industrial Technology Development Program of China(No.D040301)the National Natural Science Foundation of China(No.61571427)the Civil Aerospace Pre-research Project(No.D020214)。
文摘We investigate the influence of the source’s energy fluctuation on both computational ghost imaging and computational ghost imaging via sparsity constraint,and if the reconstruction quality will decrease with the increase of the source’s energy fluctuation.In order to overcome the problem of image degradation,a correction approach against the source’s energy fluctuation is proposed by recording the source’s fluctuation with a monitor before modulation and correcting the echo signal or the intensity of computed reference light field with the data recorded by the monitor.Both the numerical simulation and experimental results demonstrate that computational ghost imaging via sparsity constraint can be enhanced by correcting the echo signal or the intensity of computed reference light field,while only correcting the echo signal is valid for computational ghost imaging.
