Phase unwrapping is one of the key roles in fringe projection three-dimensional(3D)measurement technology.We propose a new method to achieve phase unwrapping in camera array light filed fringe projection 3D measuremen...Phase unwrapping is one of the key roles in fringe projection three-dimensional(3D)measurement technology.We propose a new method to achieve phase unwrapping in camera array light filed fringe projection 3D measurement based on deep learning.A multi-stream convolutional neural network(CNN)is proposed to learn the mapping relationship between camera array light filed wrapped phases and fringe orders of the expected central view,and is used to predict the fringe order to achieve the phase unwrapping.Experiments are performed on the light field fringe projection data generated by the simulated camera array fringe projection measurement system in Blender and by the experimental 3×3 camera array light field fringe projection system.The performance of the proposed network with light field wrapped phases using multiple directions as network input data is studied,and the advantages of phase unwrapping based on deep learning in light filed fringe projection are demonstrated.展开更多
Single-shot high-speed 3D imaging is important for reconstructions of dynamic objects.For fringe projection profilometry(FPP),however,it is still challenging to recover accurate 3D shapes of isolated objects by a sing...Single-shot high-speed 3D imaging is important for reconstructions of dynamic objects.For fringe projection profilometry(FPP),however,it is still challenging to recover accurate 3D shapes of isolated objects by a single fringe image.In this paper,we demonstrate that the deep neural networks can be trained to directly recover the absolute phase from a unique fringe image that involves spatially multiplexed fringe patterns of different frequencies.The extracted phase is free from spectrum-aliasing problem which is hard to avoid for traditional spatial-multiplexing methods.Experiments on both static and dynamic scenes show that the proposed approach is robust to object motion and can obtain high-quality 3D reconstructions of isolated objects within a single fringe image.展开更多
An efficient implementation of the topography adaptive filter based on local frequency estimation is proposed, where chirp z transform is applied to enhance the accuracy of the frequency estimation. As a by product of...An efficient implementation of the topography adaptive filter based on local frequency estimation is proposed, where chirp z transform is applied to enhance the accuracy of the frequency estimation. As a by product of this adaptive filter, the linear approximated phase model of the interferogram is employed to improve the coherence estimation. The impacts of the adaptive filter on global and local phase unwrapping algorithms are discussed. Finally, aiming at the negative effect that the adaptive filter can bring to local phase unwrapping algorithms, a fusion scheme that takes advantage of least square and several local phase unwrapping algorithms is presented.展开更多
Optically transmissive and reflective objects may have varying surface profiles,which translate to arbitrary phase profiles for light either transmitted through or reflected from the object.For high-throughput applica...Optically transmissive and reflective objects may have varying surface profiles,which translate to arbitrary phase profiles for light either transmitted through or reflected from the object.For high-throughput applications,resolving arbitrary phases and absolute heights is a key problem.To extend the ability of measuring absolute phase jumps in existing 3D imaging techniques,the dual-wavelength concept,proposed in late 1800s,has been developed in the last few decades.By adopting an extra wavelength in measurements,a synthetic wavelength,usually larger than each of the single wavelengths,can be simulated to extract large phases or height variations from micron-level to tens of centimeters scale.We review a brief history of the developments in the dualwavelength technique and present the methodology of this technique for using the phase difference and/or the phase sum.Various applications of the dual-wavelength technique are discussed,including height feature extraction from micron scale to centimeter scale in holography and interferometry,single-shot dual-wavelength digital holography for high-speed imaging,nanometer height resolution with fringe subdivision method,and applications in other novel phase imaging techniques and optical modalities.The noise sources for dualwavelength techniques for phase imaging and 3D topography are discussed,and potential ways to reduce or remove the noise are mentioned.展开更多
In this study,Differential Interferometric Synthetic Aperture Radar Interferometry(DInSAR)of artificial Corner Reflectors(CRs)were validated in the area of fast and nonlinear deformation gradient caused by active coal...In this study,Differential Interferometric Synthetic Aperture Radar Interferometry(DInSAR)of artificial Corner Reflectors(CRs)were validated in the area of fast and nonlinear deformation gradient caused by active coal longwall exploitation.Three Sentinel-1 datasets were processed using conventional DInSAR,Persistent Scatterer Interferometry(PSI),and Small BAseline Subset methods implemented in ENVI SARscape™.For evaluation,leveling and Global Navigation Satellite System(GNSS)measurements were used.Considering the challenge of snow cover,the removal of all winter images was not a successful strategy due to the long temporal baseline and strong movement,which cause phase unwrapping problems and underestimate the real deformation.The results indicate that only conventional DInSAR and SBAS with low network redundancy allow us to capture maximal deformation gradient and the root mean square error calculated between the CRs and the ground truth is on the level of 2–3 cm for the vertical and easting deformation component,respectively.For the small deformation gradient represented by the permanent GNSS station(4 cm/year),all SBAS techniques appeared to be more accurate than DInSAR,which corresponds to higher redundancy and better removal of the atmospheric signal.In contrast,DInSAR results allowed to capture information about two subsidence basins,which was not possible with SBAS and PSI approaches.展开更多
A novel reconstruction method of nanometer micro-displacement of Fabry-Perot(F-P)interference is proposed in this study.Hilbert transforms are performed for F-P interference fringes,and the obtained signal performs ta...A novel reconstruction method of nanometer micro-displacement of Fabry-Perot(F-P)interference is proposed in this study.Hilbert transforms are performed for F-P interference fringes,and the obtained signal performs tangent operation with the original signal.Finally,the validity of the proposed algorithm and the structure are verified by simulation and several experimental measurements for vibration.Results from the experiments show that the maximum relative error is 4.9%.展开更多
This paper presents an improved non-data-aided algo-rithm for carrier frequency estimation for burst M-ary PSK signals when modulation order M and training symbols are unknown. Unlike data-aided estimation, a phase cl...This paper presents an improved non-data-aided algo-rithm for carrier frequency estimation for burst M-ary PSK signals when modulation order M and training symbols are unknown. Unlike data-aided estimation, a phase clustering algorithm is used first to estimate M and modulated information is removed by a vari-able interval linear phase unwrapping. Then, a high-order correlation algorithm with proper correction is present, which reduces the probability of phase ambiguity and promotes anti-noise capability of the estimation. Simulations are given to analyze the unbiased esti-mation range, and the asymptotic performance and symbol number are needed to compare with the former algorithms. The new algo-rithm has a large estimation range close to the theoretical maximum value for non-data-aided estimation and has a better performance than earlier non-data-aided techniques for large frequency offset, low signal-to-noise ratio, and limited symbol numbers.展开更多
基金the National Natural Science Foundation of China(No.61905178)the Science&Technology Development Fund of Tianjin Education Commission for Higher Education(No.2019KJ021)the Natural Science Foundation of Tianjin(No.18JCQNJC71100)。
文摘Phase unwrapping is one of the key roles in fringe projection three-dimensional(3D)measurement technology.We propose a new method to achieve phase unwrapping in camera array light filed fringe projection 3D measurement based on deep learning.A multi-stream convolutional neural network(CNN)is proposed to learn the mapping relationship between camera array light filed wrapped phases and fringe orders of the expected central view,and is used to predict the fringe order to achieve the phase unwrapping.Experiments are performed on the light field fringe projection data generated by the simulated camera array fringe projection measurement system in Blender and by the experimental 3×3 camera array light field fringe projection system.The performance of the proposed network with light field wrapped phases using multiple directions as network input data is studied,and the advantages of phase unwrapping based on deep learning in light filed fringe projection are demonstrated.
基金This work was supported by National Natural Science Foundation of China(62075096,62005121,U21B2033)Leading Technology of Jiangsu Basic Research Plan(BK20192003)+4 种基金“333 Engineering”Research Project of Jiangsu Province(BRA2016407)Jiangsu Provincial“One belt and one road”innovation cooperation project(BZ2020007)Fundamental Research Funds for the Central Universities(30921011208,30919011222,30920032101)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX21_0273)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(JSGP202105).
文摘Single-shot high-speed 3D imaging is important for reconstructions of dynamic objects.For fringe projection profilometry(FPP),however,it is still challenging to recover accurate 3D shapes of isolated objects by a single fringe image.In this paper,we demonstrate that the deep neural networks can be trained to directly recover the absolute phase from a unique fringe image that involves spatially multiplexed fringe patterns of different frequencies.The extracted phase is free from spectrum-aliasing problem which is hard to avoid for traditional spatial-multiplexing methods.Experiments on both static and dynamic scenes show that the proposed approach is robust to object motion and can obtain high-quality 3D reconstructions of isolated objects within a single fringe image.
文摘An efficient implementation of the topography adaptive filter based on local frequency estimation is proposed, where chirp z transform is applied to enhance the accuracy of the frequency estimation. As a by product of this adaptive filter, the linear approximated phase model of the interferogram is employed to improve the coherence estimation. The impacts of the adaptive filter on global and local phase unwrapping algorithms are discussed. Finally, aiming at the negative effect that the adaptive filter can bring to local phase unwrapping algorithms, a fusion scheme that takes advantage of least square and several local phase unwrapping algorithms is presented.
文摘Optically transmissive and reflective objects may have varying surface profiles,which translate to arbitrary phase profiles for light either transmitted through or reflected from the object.For high-throughput applications,resolving arbitrary phases and absolute heights is a key problem.To extend the ability of measuring absolute phase jumps in existing 3D imaging techniques,the dual-wavelength concept,proposed in late 1800s,has been developed in the last few decades.By adopting an extra wavelength in measurements,a synthetic wavelength,usually larger than each of the single wavelengths,can be simulated to extract large phases or height variations from micron-level to tens of centimeters scale.We review a brief history of the developments in the dualwavelength technique and present the methodology of this technique for using the phase difference and/or the phase sum.Various applications of the dual-wavelength technique are discussed,including height feature extraction from micron scale to centimeter scale in holography and interferometry,single-shot dual-wavelength digital holography for high-speed imaging,nanometer height resolution with fringe subdivision method,and applications in other novel phase imaging techniques and optical modalities.The noise sources for dualwavelength techniques for phase imaging and 3D topography are discussed,and potential ways to reduce or remove the noise are mentioned.
基金The research infrastructure that has been used for computation purposes was created within the project EPOS-PL(POIR.04.02.00-14-A003/16)EPOS-PL+(POIR.04.02.00-00-C005/19-00)European Plate Observing System,funded by the Operational Programme Smart Growth 2014-2020,Priority IV:Increasing the research potential,Action 4.2:Development of modern research infrastructure of the science sector and co-financed by the European Regional Development Fund.
文摘In this study,Differential Interferometric Synthetic Aperture Radar Interferometry(DInSAR)of artificial Corner Reflectors(CRs)were validated in the area of fast and nonlinear deformation gradient caused by active coal longwall exploitation.Three Sentinel-1 datasets were processed using conventional DInSAR,Persistent Scatterer Interferometry(PSI),and Small BAseline Subset methods implemented in ENVI SARscape™.For evaluation,leveling and Global Navigation Satellite System(GNSS)measurements were used.Considering the challenge of snow cover,the removal of all winter images was not a successful strategy due to the long temporal baseline and strong movement,which cause phase unwrapping problems and underestimate the real deformation.The results indicate that only conventional DInSAR and SBAS with low network redundancy allow us to capture maximal deformation gradient and the root mean square error calculated between the CRs and the ground truth is on the level of 2–3 cm for the vertical and easting deformation component,respectively.For the small deformation gradient represented by the permanent GNSS station(4 cm/year),all SBAS techniques appeared to be more accurate than DInSAR,which corresponds to higher redundancy and better removal of the atmospheric signal.In contrast,DInSAR results allowed to capture information about two subsidence basins,which was not possible with SBAS and PSI approaches.
基金supported by the Natural Science Foundation of Northeast Petroleum University (No. 2018GPYB-03)
文摘A novel reconstruction method of nanometer micro-displacement of Fabry-Perot(F-P)interference is proposed in this study.Hilbert transforms are performed for F-P interference fringes,and the obtained signal performs tangent operation with the original signal.Finally,the validity of the proposed algorithm and the structure are verified by simulation and several experimental measurements for vibration.Results from the experiments show that the maximum relative error is 4.9%.
基金Supported by the National Natural Science Foundation of China (61001111)
文摘This paper presents an improved non-data-aided algo-rithm for carrier frequency estimation for burst M-ary PSK signals when modulation order M and training symbols are unknown. Unlike data-aided estimation, a phase clustering algorithm is used first to estimate M and modulated information is removed by a vari-able interval linear phase unwrapping. Then, a high-order correlation algorithm with proper correction is present, which reduces the probability of phase ambiguity and promotes anti-noise capability of the estimation. Simulations are given to analyze the unbiased esti-mation range, and the asymptotic performance and symbol number are needed to compare with the former algorithms. The new algo-rithm has a large estimation range close to the theoretical maximum value for non-data-aided estimation and has a better performance than earlier non-data-aided techniques for large frequency offset, low signal-to-noise ratio, and limited symbol numbers.
