The optical design of near-infrared phase contrast imaging(NI-PCI)diagnosis on HL-2A is introduced in this paper.This scheme benefits from the great progress of near-infrared laser technology and is a broadening of tr...The optical design of near-infrared phase contrast imaging(NI-PCI)diagnosis on HL-2A is introduced in this paper.This scheme benefits from the great progress of near-infrared laser technology and is a broadening of traditional phase contrast technology.This diagnostic can work as a keen tool to measure plasma wavenumber spectra by inferring string-integrated plasma density fluctuations.Design of both the front optical path which is the path before the laser transmitting into the tokamak plasma and the rear optics which is the path after the laser passing through the plasma is detailed.The 1550 nm laser is chosen as the probe beam and highprecision optical components are designed to fit the laser beam,in which a phase plate with a 194-nm-deep silver groove is the key.Compared with the conventional 10.6μm laser-based PCI system on HL-2A,NI-PCI significantly overcomes the unwanted phase scintillation effect and promotes the measurement capability of high-wavenumber turbulence with an increased maximal measurable wavenumber from 15 cm^(-1)to 32.6 cm^(-1).展开更多
In response to the scarcity of infrared aircraft samples and the tendency of traditional deep learning to overfit,a few-shot infrared aircraft classification method based on cross-correlation networks is proposed.This...In response to the scarcity of infrared aircraft samples and the tendency of traditional deep learning to overfit,a few-shot infrared aircraft classification method based on cross-correlation networks is proposed.This method combines two core modules:a simple parameter-free self-attention and cross-attention.By analyzing the self-correlation and cross-correlation between support images and query images,it achieves effective classification of infrared aircraft under few-shot conditions.The proposed cross-correlation network integrates these two modules and is trained in an end-to-end manner.The simple parameter-free self-attention is responsible for extracting the internal structure of the image while the cross-attention can calculate the cross-correlation between images further extracting and fusing the features between images.Compared with existing few-shot infrared target classification models,this model focuses on the geometric structure and thermal texture information of infrared images by modeling the semantic relevance between the features of the support set and query set,thus better attending to the target objects.Experimental results show that this method outperforms existing infrared aircraft classification methods in various classification tasks,with the highest classification accuracy improvement exceeding 3%.In addition,ablation experiments and comparative experiments also prove the effectiveness of the method.展开更多
AIM:To establish pupil diameter measurement algorithms based on infrared images that can be used in real-world clinical settings.METHODS:A total of 188 patients from outpatient clinic at He Eye Specialist Shenyang Hos...AIM:To establish pupil diameter measurement algorithms based on infrared images that can be used in real-world clinical settings.METHODS:A total of 188 patients from outpatient clinic at He Eye Specialist Shenyang Hospital from Spetember to December 2022 were included,and 13470 infrared pupil images were collected for the study.All infrared images for pupil segmentation were labeled using the Labelme software.The computation of pupil diameter is divided into four steps:image pre-processing,pupil identification and localization,pupil segmentation,and diameter calculation.Two major models are used in the computation process:the modified YoloV3 and Deeplabv 3+models,which must be trained beforehand.RESULTS:The test dataset included 1348 infrared pupil images.On the test dataset,the modified YoloV3 model had a detection rate of 99.98% and an average precision(AP)of 0.80 for pupils.The DeeplabV3+model achieved a background intersection over union(IOU)of 99.23%,a pupil IOU of 93.81%,and a mean IOU of 96.52%.The pupil diameters in the test dataset ranged from 20 to 56 pixels,with a mean of 36.06±6.85 pixels.The absolute error in pupil diameters between predicted and actual values ranged from 0 to 7 pixels,with a mean absolute error(MAE)of 1.06±0.96 pixels.CONCLUSION:This study successfully demonstrates a robust infrared image-based pupil diameter measurement algorithm,proven to be highly accurate and reliable for clinical application.展开更多
A novel portable infrared imaging system based on uncooled focal plane array and programmable system-on-chip（SoC）was proposed.The latest Xilinx Zynq-7000 was used to integrate the main part of the system into a sing...A novel portable infrared imaging system based on uncooled focal plane array and programmable system-on-chip（SoC）was proposed.The latest Xilinx Zynq-7000 was used to integrate the main part of the system into a single SoC.Parallel arithmetic units and digital modules were implemented on the programmable logic（PL）of Zynq-7000 to decrease system size and ensure the real-time p nonuniformity correction,while programs running on the processing system（PS）of Zynq-7000 controlled the system work flow and provided human-machine interfaces using open-source software such as Linux and OpenCV.Meanwhile,industry standard advanced extendable interface（AXI）buses were adopted to encapsulating standardized IP cores and build high speed data exchange bridges between units within Zynq-7000.Test results indicate that the image quality and real-time performance of the system can meet application requirements.And it provided a more flexible and extendable solution for evaluating and deploying infrared image enhancement and nonuniformity correction algorithms.展开更多
Detection of local strain at the nanometer scale with high sensitivity remains challenging.Here we report near-field infrared nano-imaging of local strains in bilayer graphene by probing strain-induced shifts of phono...Detection of local strain at the nanometer scale with high sensitivity remains challenging.Here we report near-field infrared nano-imaging of local strains in bilayer graphene by probing strain-induced shifts of phonon frequency.As a non-polar crystal,intrinsic bilayer graphene possesses little infrared response at its transverse optical phonon frequency.The reported optical detection of local strain is enabled by applying a vertical electrical field that breaks the symmetry of the two graphene layers and introduces finite electrical dipole moment to graphene phonon.The activated phonon further interacts with continuum electronic transitions,and generates a strong Fano resonance.The resulted Fano resonance features a very sharp near-field infrared scattering peak,which leads to an extraordinary sensitivity of-0.002%for the strain detection.Our results demonstrate the first nano-scale near-field Fano resonance,provide a new way to probe local strains with high sensitivity in non-polar crystals,and open exciting possibilities for studying strain-induced rich phenomena.展开更多
An equivalent circuit model to the substrate-free focal plane array(FPA)is established.Using this fast and effective model,the performance of infrared(IR)imaging at atmospheric pressure is investigated and it is found...An equivalent circuit model to the substrate-free focal plane array(FPA)is established.Using this fast and effective model,the performance of infrared(IR)imaging at atmospheric pressure is investigated and it is found that the substrate-free FPA has the ability of IR imaging at atmospheric pressure,whereas it has a slightly degraded noise equivalent temperature difference(NETD)as compared with IR imaging under a high vacuum.This feature is also identified experimentally by a substrate-free FPA with pixel size of 50×50μm^(2).The NETDs are measured to be 160 mK at 10^(-2) Pa pressure and 1.08 K at atmospheric pressure.展开更多
Objective: To scan all the possibly diseased areas of an organ, a new method of digital infrared thermal imaging (DITI) system was designed on the basis of medical theory. Methods: This new method of DITT is operated ...Objective: To scan all the possibly diseased areas of an organ, a new method of digital infrared thermal imaging (DITI) system was designed on the basis of medical theory. Methods: This new method of DITT is operated in 2 steps; the image is sharpened with wavelet transformation and then the image is divided into normal and possibly diseased areas with Fuzzy clustering. Results: It was found for a comparison between the old and new methods that the new method is more reliable in clinical practice and takes less time to complete a computation. Conclusion : The new model of DITI system can be used clinically to improve the diagnostic accuracy of breast disease.展开更多
An infrared imaging bolometer diagnostic has been upgraded recently to be adapted for the complications of the signal-to-noise ratio arising from the low level of plasma radiation and high reflectivity of low energy p...An infrared imaging bolometer diagnostic has been upgraded recently to be adapted for the complications of the signal-to-noise ratio arising from the low level of plasma radiation and high reflectivity of low energy photon（〈6.2 eV）.It utilizes a platinum foil,blackened on both sides with graphite spray,as the bolometer detector.The advantage of the blackened foil is the light absorption extending into the infrared.After a careful calibration of the foil,the incident power density distribution on the foil is determined by solving the heat diffusion equation with a numerical technique.The local plasma radiated power density is reconstructed with a minimum fisher information regularization method by assuming plasma emission toroidal symmetry.Comparisons of the results and the profiles measured by an ordinary bolometric detector demonstrate that this method is good enough to provide the plasma radiated power pattern.The typical plasma radiated power density distribution before and after high mode（H-mode） transition is firstly reconstructed with the infrared imaging bolometer.Moreover,during supersonic molecular beam injection（SMBI）,an enhanced radiation region is observed at the edge of the plasma.展开更多
Real-time polarization medium-wave infrared(MIR)optical imaging systems enable the acquisition of infrared and polarization information for a target.At present,real-time polarization MIR devices face the following pro...Real-time polarization medium-wave infrared(MIR)optical imaging systems enable the acquisition of infrared and polarization information for a target.At present,real-time polarization MIR devices face the following problems:poor real-time performance,low transmission and high requirements for fabrication and integration.Herein,we aim to improve the performance of real-time polarization imaging systems in the MIR waveband and solve the above-mentioned defects.Therefore,we propose a MIR polarization imaging system to achieve real-time polarization-modulated imaging with high transmission as well as improved performance based on a pixel-wise metasurface micro-polarization array(PMMPA).The PMMPA element comprises several linear polarization(LP)filters with different polarization angles.The optimization results demonstrate that the transmittance of the center field of view for the LP filters is up to 77%at a wavelength of4.0μm and an extinction ratio of 88 d B.In addition,a near-diffraction-limited real-time MIR imaging optical system is designed with a field of view of 5°and an F-number of 2.The simulation results show that an MIR polarization imaging system with excellent real-time performance and high transmission is achieved by using the optimized PMMPA element.Therefore,the method is compatible with the available optical system design technologies and provides a way to realize real-time polarization imaging in MIR wavebands.展开更多
To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation f...To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation for input image with angle difference between them. A hi erarchical feature matching algorithm was adopted to get the final transform parameters between the two images. The simulation results for two infrared images show that the method can effectively, quickly and accurately register images and be antinoise to some extent.展开更多
Infrared small target detection is a common task in infrared image processing.Under limited computa⁃tional resources.Traditional methods for infrared small target detection face a trade-off between the detection rate ...Infrared small target detection is a common task in infrared image processing.Under limited computa⁃tional resources.Traditional methods for infrared small target detection face a trade-off between the detection rate and the accuracy.A fast infrared small target detection method tailored for resource-constrained conditions is pro⁃posed for the YOLOv5s model.This method introduces an additional small target detection head and replaces the original Intersection over Union(IoU)metric with Normalized Wasserstein Distance(NWD),while considering both the detection accuracy and the detection speed of infrared small targets.Experimental results demonstrate that the proposed algorithm achieves a maximum effective detection speed of 95 FPS on a 15 W TPU,while reach⁃ing a maximum effective detection accuracy of 91.9 AP@0.5,effectively improving the efficiency of infrared small target detection under resource-constrained conditions.展开更多
It is crucial to maintain the safe and stable operation of distribution transformers,which constitute a key part of power systems.In the event of transformer failure,the fault type must be diagnosed in a timely and ac...It is crucial to maintain the safe and stable operation of distribution transformers,which constitute a key part of power systems.In the event of transformer failure,the fault type must be diagnosed in a timely and accurate manner.To this end,a transformer fault diagnosis method based on infrared image processing and semi-supervised learning is proposed herein.First,we perform feature extraction on the collected infrared-image data to extract temperature,texture,and shape features as the model reference vectors.Then,a generative adversarial network(GAN)is constructed to generate synthetic samples for the minority subset of labelled samples.The proposed method can learn information from unlabeled sample data,unlike conventional supervised learning methods.Subsequently,a semi-supervised graph model is trained on the entire dataset,i.e.,both labeled and unlabeled data.Finally,we test the proposed model on an actual dataset collected from a Chinese electricity provider.The experimental results show that the use of feature extraction,sample generation,and semi-supervised learning model can improve the accuracy of transformer fault classification.This verifies the effectiveness of the proposed method.展开更多
Metasurfaces in the long wave infrared(LWIR)spectrum hold great potential for applications in ther-mal imaging,atmospheric remote sensing,and target identification,among others.In this study,we designed and experiment...Metasurfaces in the long wave infrared(LWIR)spectrum hold great potential for applications in ther-mal imaging,atmospheric remote sensing,and target identification,among others.In this study,we designed and experimentally demonstrated a 4 mm size,all-silicon metasurface metalens with large depth of focus opera-tional across a broadband range from 9µm to 11.5µm.The experimental results confirm effective focusing and imaging capabilities of the metalens in LWIR region,thus paving the way for practical LWIR applications of met-alens technology.展开更多
To improve the quality of the infrared image and enhance the information of the object,a dual band infrared image fusion method based on feature extraction and a novel multiple pulse coupled neural network(multi-PCNN)...To improve the quality of the infrared image and enhance the information of the object,a dual band infrared image fusion method based on feature extraction and a novel multiple pulse coupled neural network(multi-PCNN)is proposed.In this multi-PCNN fusion scheme,the auxiliary PCNN which captures the characteristics of feature image extracting from the infrared image is used to modulate the main PCNN,whose input could be original infrared image.Meanwhile,to make the PCNN fusion effect consistent with the human vision system,Laplacian energy is adopted to obtain the value of adaptive linking strength in PCNN.After that,the original dual band infrared images are reconstructed by using a weight fusion rule with the fire mapping images generated by the main PCNNs to obtain the fused image.Compared to wavelet transforms,Laplacian pyramids and traditional multi-PCNNs,fusion images based on our method have more information,rich details and clear edges.展开更多
As the representative of flexibility in optical imaging media,in recent years,fiber bundles have emerged as a promising architecture in the development of compact visual systems.Dedicated to tackling the problems of u...As the representative of flexibility in optical imaging media,in recent years,fiber bundles have emerged as a promising architecture in the development of compact visual systems.Dedicated to tackling the problems of universal honeycomb artifacts and low signal-to-noise ratio(SNR)imaging in fiber bundles,the iterative super-resolution reconstruction network based on a physical model is proposed.Under the constraint of solving the two subproblems of data fidelity and prior regularization term alternately,the network can efficiently“regenerate”the lost spatial resolution with deep learning.By building and calibrating a dual-path imaging system,the real-world dataset where paired low-resolution(LR)-high-resolution(HR)images on the same scene can be generated simultaneously.Numerical results on both the United States Air Force(USAF)resolution target and complex target objects demonstrate that the algorithm can restore high-contrast images without pixilated noise.On the basis of super-resolution reconstruction,compound eye image composition based on fiber bundle is also embedded in this paper for the actual imaging requirements.The proposed work is the first to apply a physical model-based deep learning network to fiber bundle imaging in the infrared band,effectively promoting the engineering application of thermal radiation detection.展开更多
Heat transfer and temperature evolution in overburden fracture and ground fissures are one of the essential topics for the identification of ground fissures via unmanned aerial vehicle(UAV) infrared imager. In this st...Heat transfer and temperature evolution in overburden fracture and ground fissures are one of the essential topics for the identification of ground fissures via unmanned aerial vehicle(UAV) infrared imager. In this study, discrete element software UDEC was employed to investigate the overburden fracture field under different mining conditions. Multiphysics software COMSOL were employed to investigate heat transfer and temperature evolution of overburden fracture and ground fissures under the influence of mining condition, fissure depth, fissure width, and month alternation. The UAV infrared field measurements also provided a calibration for numerical simulation. The results showed that for ground fissures connected to underground goaf(Fissure Ⅰ), the temperature difference increased with larger mining height and shallow buried depth. In addition, Fissure Ⅰ located in the boundary of the goaf have a greater temperature difference and is easier to be identified than fissures located above the mining goaf. For ground fissures having no connection to underground goaf(Fissure Ⅱ), the heat transfer is affected by the internal resistance of the overlying strata fracture when the depth of Fissure Ⅱ is greater than10 m, the temperature of Fissure Ⅱ gradually equals to the ground temperature as the fissures’ depth increases, and the fissures are difficult to be identified. The identification effect is most obvious for fissures larger than 16 cm under the same depth. In spring and summer, UAV infrared identification of mining fissures should be carried out during nighttime. This study provides the basis for the optimal time and season for the UAV infrared identification of different types of mining ground fissures.展开更多
The high-frequency components in the traditional multi-scale transform method are approximately sparse, which can represent different information of the details. But in the low-frequency component, the coefficients ar...The high-frequency components in the traditional multi-scale transform method are approximately sparse, which can represent different information of the details. But in the low-frequency component, the coefficients around the zero value are very few, so we cannot sparsely represent low-frequency image information. The low-frequency component contains the main energy of the image and depicts the profile of the image. Direct fusion of the low-frequency component will not be conducive to obtain highly accurate fusion result. Therefore, this paper presents an infrared and visible image fusion method combining the multi-scale and top-hat transforms. On one hand, the new top-hat-transform can effectively extract the salient features of the low-frequency component. On the other hand, the multi-scale transform can extract highfrequency detailed information in multiple scales and from diverse directions. The combination of the two methods is conducive to the acquisition of more characteristics and more accurate fusion results. Among them, for the low-frequency component, a new type of top-hat transform is used to extract low-frequency features, and then different fusion rules are applied to fuse the low-frequency features and low-frequency background; for high-frequency components, the product of characteristics method is used to integrate the detailed information in high-frequency. Experimental results show that the proposed algorithm can obtain more detailed information and clearer infrared target fusion results than the traditional multiscale transform methods. Compared with the state-of-the-art fusion methods based on sparse representation, the proposed algorithm is simple and efficacious, and the time consumption is significantly reduced.展开更多
Infrared-visible image fusion plays an important role in multi-source data fusion,which has the advantage of integrating useful information from multi-source sensors.However,there are still challenges in target enhanc...Infrared-visible image fusion plays an important role in multi-source data fusion,which has the advantage of integrating useful information from multi-source sensors.However,there are still challenges in target enhancement and visual improvement.To deal with these problems,a sub-regional infrared-visible image fusion method(SRF)is proposed.First,morphology and threshold segmentation is applied to extract targets interested in infrared images.Second,the infrared back-ground is reconstructed based on extracted targets and the visible image.Finally,target and back-ground regions are fused using a multi-scale transform.Experimental results are obtained using public data for comparison and evaluation,which demonstrate that the proposed SRF has poten-tial benefits over other methods.展开更多
Infrared image recognition plays an important role in the inspection of power equipment.Existing technologies dedicated to this purpose often require manually selected features,which are not transferable and interpret...Infrared image recognition plays an important role in the inspection of power equipment.Existing technologies dedicated to this purpose often require manually selected features,which are not transferable and interpretable,and have limited training data.To address these limitations,this paper proposes an automatic infrared image recognition framework,which includes an object recognition module based on a deep self-attention network and a temperature distribution identification module based on a multi-factor similarity calculation.First,the features of an input image are extracted and embedded using a multi-head attention encoding-decoding mechanism.Thereafter,the embedded features are used to predict the equipment component category and location.In the located area,preliminary segmentation is performed.Finally,similar areas are gradually merged,and the temperature distribution of the equipment is obtained to identify a fault.Our experiments indicate that the proposed method demonstrates significantly improved accuracy compared with other related methods and,hence,provides a good reference for the automation of power equipment inspection.展开更多
Infrared scene simulation has extensive applications in military and civil fields. Based on a certain experimental environment,object-oriented graphics rendering engine（ OGRE） is utilized to simulate a real three-di...Infrared scene simulation has extensive applications in military and civil fields. Based on a certain experimental environment,object-oriented graphics rendering engine（ OGRE） is utilized to simulate a real three-dimensional infrared complex scene. First,the target radiation of each part is calculated based on our experimental data. Then through the analysis of the radiation characteristics of targets and related material,an infrared texture library is established and the 3ds Max software is applied to establish an infrared radiation model.Finally,a real complex infrared scene is created by using the OGRE engine image rendering technology and graphic processing unit（ GPU） programmable pipeline technology. The results show that the simulation images are very similar to real images and are good supplements to real data.展开更多
基金supported by the National Key Research and Development Program of China(Nos.2019YFE03090100 and 2022YFE03100002)National Natural Science Foundation of China(No.12075241)。
文摘The optical design of near-infrared phase contrast imaging(NI-PCI)diagnosis on HL-2A is introduced in this paper.This scheme benefits from the great progress of near-infrared laser technology and is a broadening of traditional phase contrast technology.This diagnostic can work as a keen tool to measure plasma wavenumber spectra by inferring string-integrated plasma density fluctuations.Design of both the front optical path which is the path before the laser transmitting into the tokamak plasma and the rear optics which is the path after the laser passing through the plasma is detailed.The 1550 nm laser is chosen as the probe beam and highprecision optical components are designed to fit the laser beam,in which a phase plate with a 194-nm-deep silver groove is the key.Compared with the conventional 10.6μm laser-based PCI system on HL-2A,NI-PCI significantly overcomes the unwanted phase scintillation effect and promotes the measurement capability of high-wavenumber turbulence with an increased maximal measurable wavenumber from 15 cm^(-1)to 32.6 cm^(-1).
基金Supported by the National Pre-research Program during the 14th Five-Year Plan(514010405)。
文摘In response to the scarcity of infrared aircraft samples and the tendency of traditional deep learning to overfit,a few-shot infrared aircraft classification method based on cross-correlation networks is proposed.This method combines two core modules:a simple parameter-free self-attention and cross-attention.By analyzing the self-correlation and cross-correlation between support images and query images,it achieves effective classification of infrared aircraft under few-shot conditions.The proposed cross-correlation network integrates these two modules and is trained in an end-to-end manner.The simple parameter-free self-attention is responsible for extracting the internal structure of the image while the cross-attention can calculate the cross-correlation between images further extracting and fusing the features between images.Compared with existing few-shot infrared target classification models,this model focuses on the geometric structure and thermal texture information of infrared images by modeling the semantic relevance between the features of the support set and query set,thus better attending to the target objects.Experimental results show that this method outperforms existing infrared aircraft classification methods in various classification tasks,with the highest classification accuracy improvement exceeding 3%.In addition,ablation experiments and comparative experiments also prove the effectiveness of the method.
文摘AIM:To establish pupil diameter measurement algorithms based on infrared images that can be used in real-world clinical settings.METHODS:A total of 188 patients from outpatient clinic at He Eye Specialist Shenyang Hospital from Spetember to December 2022 were included,and 13470 infrared pupil images were collected for the study.All infrared images for pupil segmentation were labeled using the Labelme software.The computation of pupil diameter is divided into four steps:image pre-processing,pupil identification and localization,pupil segmentation,and diameter calculation.Two major models are used in the computation process:the modified YoloV3 and Deeplabv 3+models,which must be trained beforehand.RESULTS:The test dataset included 1348 infrared pupil images.On the test dataset,the modified YoloV3 model had a detection rate of 99.98% and an average precision(AP)of 0.80 for pupils.The DeeplabV3+model achieved a background intersection over union(IOU)of 99.23%,a pupil IOU of 93.81%,and a mean IOU of 96.52%.The pupil diameters in the test dataset ranged from 20 to 56 pixels,with a mean of 36.06±6.85 pixels.The absolute error in pupil diameters between predicted and actual values ranged from 0 to 7 pixels,with a mean absolute error(MAE)of 1.06±0.96 pixels.CONCLUSION:This study successfully demonstrates a robust infrared image-based pupil diameter measurement algorithm,proven to be highly accurate and reliable for clinical application.
文摘A novel portable infrared imaging system based on uncooled focal plane array and programmable system-on-chip（SoC）was proposed.The latest Xilinx Zynq-7000 was used to integrate the main part of the system into a single SoC.Parallel arithmetic units and digital modules were implemented on the programmable logic（PL）of Zynq-7000 to decrease system size and ensure the real-time p nonuniformity correction,while programs running on the processing system（PS）of Zynq-7000 controlled the system work flow and provided human-machine interfaces using open-source software such as Linux and OpenCV.Meanwhile,industry standard advanced extendable interface（AXI）buses were adopted to encapsulating standardized IP cores and build high speed data exchange bridges between units within Zynq-7000.Test results indicate that the image quality and real-time performance of the system can meet application requirements.And it provided a more flexible and extendable solution for evaluating and deploying infrared image enhancement and nonuniformity correction algorithms.
基金Supported by the National Key Research and Development Program of China (Grant No.2016YFA0302001)the National Natural Science Foundation of China (Grant Nos.11774224,12074244,11521404,and 61701394)+1 种基金support from the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learningadditional support from a Shanghai talent program。
文摘Detection of local strain at the nanometer scale with high sensitivity remains challenging.Here we report near-field infrared nano-imaging of local strains in bilayer graphene by probing strain-induced shifts of phonon frequency.As a non-polar crystal,intrinsic bilayer graphene possesses little infrared response at its transverse optical phonon frequency.The reported optical detection of local strain is enabled by applying a vertical electrical field that breaks the symmetry of the two graphene layers and introduces finite electrical dipole moment to graphene phonon.The activated phonon further interacts with continuum electronic transitions,and generates a strong Fano resonance.The resulted Fano resonance features a very sharp near-field infrared scattering peak,which leads to an extraordinary sensitivity of-0.002%for the strain detection.Our results demonstrate the first nano-scale near-field Fano resonance,provide a new way to probe local strains with high sensitivity in non-polar crystals,and open exciting possibilities for studying strain-induced rich phenomena.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11072233,11102201 and 11127201the China Postdoctoral Science Foundation under Grant No 20100480684+2 种基金the Fundamental Research Funds for the Central Universities under Grant No WK2090050017the Natural Science Foundation of Jiangsu Province under Grant No BK2011373the National Basic Research Program of China under Grant No 2006CB300404.
文摘An equivalent circuit model to the substrate-free focal plane array(FPA)is established.Using this fast and effective model,the performance of infrared(IR)imaging at atmospheric pressure is investigated and it is found that the substrate-free FPA has the ability of IR imaging at atmospheric pressure,whereas it has a slightly degraded noise equivalent temperature difference(NETD)as compared with IR imaging under a high vacuum.This feature is also identified experimentally by a substrate-free FPA with pixel size of 50×50μm^(2).The NETDs are measured to be 160 mK at 10^(-2) Pa pressure and 1.08 K at atmospheric pressure.
文摘Objective: To scan all the possibly diseased areas of an organ, a new method of digital infrared thermal imaging (DITI) system was designed on the basis of medical theory. Methods: This new method of DITT is operated in 2 steps; the image is sharpened with wavelet transformation and then the image is divided into normal and possibly diseased areas with Fuzzy clustering. Results: It was found for a comparison between the old and new methods that the new method is more reliable in clinical practice and takes less time to complete a computation. Conclusion : The new model of DITI system can be used clinically to improve the diagnostic accuracy of breast disease.
基金supported by National Natural Science Foundation of China(Nos.10805016 and 11175061)the Chinese National Fusion Projectfor ITER(No.2014GB109001)
文摘An infrared imaging bolometer diagnostic has been upgraded recently to be adapted for the complications of the signal-to-noise ratio arising from the low level of plasma radiation and high reflectivity of low energy photon（〈6.2 eV）.It utilizes a platinum foil,blackened on both sides with graphite spray,as the bolometer detector.The advantage of the blackened foil is the light absorption extending into the infrared.After a careful calibration of the foil,the incident power density distribution on the foil is determined by solving the heat diffusion equation with a numerical technique.The local plasma radiated power density is reconstructed with a minimum fisher information regularization method by assuming plasma emission toroidal symmetry.Comparisons of the results and the profiles measured by an ordinary bolometric detector demonstrate that this method is good enough to provide the plasma radiated power pattern.The typical plasma radiated power density distribution before and after high mode（H-mode） transition is firstly reconstructed with the infrared imaging bolometer.Moreover,during supersonic molecular beam injection（SMBI）,an enhanced radiation region is observed at the edge of the plasma.
基金Project supported by the National Key R&D Program of China(Grant No.SKLA02020001A05)。
文摘Real-time polarization medium-wave infrared(MIR)optical imaging systems enable the acquisition of infrared and polarization information for a target.At present,real-time polarization MIR devices face the following problems:poor real-time performance,low transmission and high requirements for fabrication and integration.Herein,we aim to improve the performance of real-time polarization imaging systems in the MIR waveband and solve the above-mentioned defects.Therefore,we propose a MIR polarization imaging system to achieve real-time polarization-modulated imaging with high transmission as well as improved performance based on a pixel-wise metasurface micro-polarization array(PMMPA).The PMMPA element comprises several linear polarization(LP)filters with different polarization angles.The optimization results demonstrate that the transmittance of the center field of view for the LP filters is up to 77%at a wavelength of4.0μm and an extinction ratio of 88 d B.In addition,a near-diffraction-limited real-time MIR imaging optical system is designed with a field of view of 5°and an F-number of 2.The simulation results show that an MIR polarization imaging system with excellent real-time performance and high transmission is achieved by using the optimized PMMPA element.Therefore,the method is compatible with the available optical system design technologies and provides a way to realize real-time polarization imaging in MIR wavebands.
文摘To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation for input image with angle difference between them. A hi erarchical feature matching algorithm was adopted to get the final transform parameters between the two images. The simulation results for two infrared images show that the method can effectively, quickly and accurately register images and be antinoise to some extent.
文摘Infrared small target detection is a common task in infrared image processing.Under limited computa⁃tional resources.Traditional methods for infrared small target detection face a trade-off between the detection rate and the accuracy.A fast infrared small target detection method tailored for resource-constrained conditions is pro⁃posed for the YOLOv5s model.This method introduces an additional small target detection head and replaces the original Intersection over Union(IoU)metric with Normalized Wasserstein Distance(NWD),while considering both the detection accuracy and the detection speed of infrared small targets.Experimental results demonstrate that the proposed algorithm achieves a maximum effective detection speed of 95 FPS on a 15 W TPU,while reach⁃ing a maximum effective detection accuracy of 91.9 AP@0.5,effectively improving the efficiency of infrared small target detection under resource-constrained conditions.
基金supported by China Southern Power Grid Co.Ltd.science and technology project(Research on the theory,technology and application of stereoscopic disaster defense for power distribution network in large city,GZHKJXM20180060)National Natural Science Foundation of China(No.51477100).
文摘It is crucial to maintain the safe and stable operation of distribution transformers,which constitute a key part of power systems.In the event of transformer failure,the fault type must be diagnosed in a timely and accurate manner.To this end,a transformer fault diagnosis method based on infrared image processing and semi-supervised learning is proposed herein.First,we perform feature extraction on the collected infrared-image data to extract temperature,texture,and shape features as the model reference vectors.Then,a generative adversarial network(GAN)is constructed to generate synthetic samples for the minority subset of labelled samples.The proposed method can learn information from unlabeled sample data,unlike conventional supervised learning methods.Subsequently,a semi-supervised graph model is trained on the entire dataset,i.e.,both labeled and unlabeled data.Finally,we test the proposed model on an actual dataset collected from a Chinese electricity provider.The experimental results show that the use of feature extraction,sample generation,and semi-supervised learning model can improve the accuracy of transformer fault classification.This verifies the effectiveness of the proposed method.
基金Supported by National Key R&D Program of China(2021YFA0715500)National Natural Science Foundation of China(NSFC)(12227901)+1 种基金Strategic Priority Research Program(B)of the Chinese Academy of Sciences(XDB0580000)Chinese Academy of Sciences President's In-ternational Fellowship Initiative(2021PT0007).
文摘Metasurfaces in the long wave infrared(LWIR)spectrum hold great potential for applications in ther-mal imaging,atmospheric remote sensing,and target identification,among others.In this study,we designed and experimentally demonstrated a 4 mm size,all-silicon metasurface metalens with large depth of focus opera-tional across a broadband range from 9µm to 11.5µm.The experimental results confirm effective focusing and imaging capabilities of the metalens in LWIR region,thus paving the way for practical LWIR applications of met-alens technology.
基金Supported by the National Natural Science Foundation of China(60905012,60572058)
文摘To improve the quality of the infrared image and enhance the information of the object,a dual band infrared image fusion method based on feature extraction and a novel multiple pulse coupled neural network(multi-PCNN)is proposed.In this multi-PCNN fusion scheme,the auxiliary PCNN which captures the characteristics of feature image extracting from the infrared image is used to modulate the main PCNN,whose input could be original infrared image.Meanwhile,to make the PCNN fusion effect consistent with the human vision system,Laplacian energy is adopted to obtain the value of adaptive linking strength in PCNN.After that,the original dual band infrared images are reconstructed by using a weight fusion rule with the fire mapping images generated by the main PCNNs to obtain the fused image.Compared to wavelet transforms,Laplacian pyramids and traditional multi-PCNNs,fusion images based on our method have more information,rich details and clear edges.
基金the National Natural Science Foundation of China(Grant Nos.61905115,62105151,62175109,U21B2033)Leading Technology of Jiangsu Basic Research Plan(Grant No.BK20192003)+2 种基金Youth Foundation of Jiangsu Province(Grant Nos.BK20190445,BK20210338)Fundamental Research Funds for the Central Universities(Grant No.30920032101)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(Grant No.JSGP202105)to provide fund for conducting experiments。
文摘As the representative of flexibility in optical imaging media,in recent years,fiber bundles have emerged as a promising architecture in the development of compact visual systems.Dedicated to tackling the problems of universal honeycomb artifacts and low signal-to-noise ratio(SNR)imaging in fiber bundles,the iterative super-resolution reconstruction network based on a physical model is proposed.Under the constraint of solving the two subproblems of data fidelity and prior regularization term alternately,the network can efficiently“regenerate”the lost spatial resolution with deep learning.By building and calibrating a dual-path imaging system,the real-world dataset where paired low-resolution(LR)-high-resolution(HR)images on the same scene can be generated simultaneously.Numerical results on both the United States Air Force(USAF)resolution target and complex target objects demonstrate that the algorithm can restore high-contrast images without pixilated noise.On the basis of super-resolution reconstruction,compound eye image composition based on fiber bundle is also embedded in this paper for the actual imaging requirements.The proposed work is the first to apply a physical model-based deep learning network to fiber bundle imaging in the infrared band,effectively promoting the engineering application of thermal radiation detection.
基金supported by the National Natural Science Foundation of China(Nos.52225402 and U1910206).
文摘Heat transfer and temperature evolution in overburden fracture and ground fissures are one of the essential topics for the identification of ground fissures via unmanned aerial vehicle(UAV) infrared imager. In this study, discrete element software UDEC was employed to investigate the overburden fracture field under different mining conditions. Multiphysics software COMSOL were employed to investigate heat transfer and temperature evolution of overburden fracture and ground fissures under the influence of mining condition, fissure depth, fissure width, and month alternation. The UAV infrared field measurements also provided a calibration for numerical simulation. The results showed that for ground fissures connected to underground goaf(Fissure Ⅰ), the temperature difference increased with larger mining height and shallow buried depth. In addition, Fissure Ⅰ located in the boundary of the goaf have a greater temperature difference and is easier to be identified than fissures located above the mining goaf. For ground fissures having no connection to underground goaf(Fissure Ⅱ), the heat transfer is affected by the internal resistance of the overlying strata fracture when the depth of Fissure Ⅱ is greater than10 m, the temperature of Fissure Ⅱ gradually equals to the ground temperature as the fissures’ depth increases, and the fissures are difficult to be identified. The identification effect is most obvious for fissures larger than 16 cm under the same depth. In spring and summer, UAV infrared identification of mining fissures should be carried out during nighttime. This study provides the basis for the optimal time and season for the UAV infrared identification of different types of mining ground fissures.
基金Project supported by the National Natural Science Foundation of China(Grant No.61402368)Aerospace Support Fund,China(Grant No.2017-HT-XGD)Aerospace Science and Technology Innovation Foundation,China(Grant No.2017 ZD 53047)
文摘The high-frequency components in the traditional multi-scale transform method are approximately sparse, which can represent different information of the details. But in the low-frequency component, the coefficients around the zero value are very few, so we cannot sparsely represent low-frequency image information. The low-frequency component contains the main energy of the image and depicts the profile of the image. Direct fusion of the low-frequency component will not be conducive to obtain highly accurate fusion result. Therefore, this paper presents an infrared and visible image fusion method combining the multi-scale and top-hat transforms. On one hand, the new top-hat-transform can effectively extract the salient features of the low-frequency component. On the other hand, the multi-scale transform can extract highfrequency detailed information in multiple scales and from diverse directions. The combination of the two methods is conducive to the acquisition of more characteristics and more accurate fusion results. Among them, for the low-frequency component, a new type of top-hat transform is used to extract low-frequency features, and then different fusion rules are applied to fuse the low-frequency features and low-frequency background; for high-frequency components, the product of characteristics method is used to integrate the detailed information in high-frequency. Experimental results show that the proposed algorithm can obtain more detailed information and clearer infrared target fusion results than the traditional multiscale transform methods. Compared with the state-of-the-art fusion methods based on sparse representation, the proposed algorithm is simple and efficacious, and the time consumption is significantly reduced.
基金supported by the China Postdoctoral Science Foundation Funded Project(No.2021M690385)the National Natural Science Foundation of China(No.62101045).
文摘Infrared-visible image fusion plays an important role in multi-source data fusion,which has the advantage of integrating useful information from multi-source sensors.However,there are still challenges in target enhancement and visual improvement.To deal with these problems,a sub-regional infrared-visible image fusion method(SRF)is proposed.First,morphology and threshold segmentation is applied to extract targets interested in infrared images.Second,the infrared back-ground is reconstructed based on extracted targets and the visible image.Finally,target and back-ground regions are fused using a multi-scale transform.Experimental results are obtained using public data for comparison and evaluation,which demonstrate that the proposed SRF has poten-tial benefits over other methods.
基金This work was supported by National Key R&D Program of China(2019YFE0102900).
文摘Infrared image recognition plays an important role in the inspection of power equipment.Existing technologies dedicated to this purpose often require manually selected features,which are not transferable and interpretable,and have limited training data.To address these limitations,this paper proposes an automatic infrared image recognition framework,which includes an object recognition module based on a deep self-attention network and a temperature distribution identification module based on a multi-factor similarity calculation.First,the features of an input image are extracted and embedded using a multi-head attention encoding-decoding mechanism.Thereafter,the embedded features are used to predict the equipment component category and location.In the located area,preliminary segmentation is performed.Finally,similar areas are gradually merged,and the temperature distribution of the equipment is obtained to identify a fault.Our experiments indicate that the proposed method demonstrates significantly improved accuracy compared with other related methods and,hence,provides a good reference for the automation of power equipment inspection.
基金Supported by the National Twelfth Five-Year Project(40405050303)
文摘Infrared scene simulation has extensive applications in military and civil fields. Based on a certain experimental environment,object-oriented graphics rendering engine（ OGRE） is utilized to simulate a real three-dimensional infrared complex scene. First,the target radiation of each part is calculated based on our experimental data. Then through the analysis of the radiation characteristics of targets and related material,an infrared texture library is established and the 3ds Max software is applied to establish an infrared radiation model.Finally,a real complex infrared scene is created by using the OGRE engine image rendering technology and graphic processing unit（ GPU） programmable pipeline technology. The results show that the simulation images are very similar to real images and are good supplements to real data.
