Using 2-dicyanomethylene-3-cyano-4,5,5-trimethyl-2,5-dihydrofuran(TCF)as a near-infrared fluorescent chromophore,we designed and synthesized a TCF-based fluorescent probe TCF-NS by introducing 2,4-dinitrophenyl ether ...Using 2-dicyanomethylene-3-cyano-4,5,5-trimethyl-2,5-dihydrofuran(TCF)as a near-infrared fluorescent chromophore,we designed and synthesized a TCF-based fluorescent probe TCF-NS by introducing 2,4-dinitrophenyl ether as the recognized site for H_(2)S.The probe TCF-NS displayed a rapid-response fluorescent against H_(2)S with high sensitivity and selection but had no significant fluorescence response to other biothiols.Furthermore,TCF-NS was applied to sense H_(2)S in living cells successfully with minimized cytotoxicity and a large Stokes shift.展开更多
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
A novel image fusion network framework with an autonomous encoder and decoder is suggested to increase thevisual impression of fused images by improving the quality of infrared and visible light picture fusion. The ne...A novel image fusion network framework with an autonomous encoder and decoder is suggested to increase thevisual impression of fused images by improving the quality of infrared and visible light picture fusion. The networkcomprises an encoder module, fusion layer, decoder module, and edge improvementmodule. The encoder moduleutilizes an enhanced Inception module for shallow feature extraction, then combines Res2Net and Transformerto achieve deep-level co-extraction of local and global features from the original picture. An edge enhancementmodule (EEM) is created to extract significant edge features. A modal maximum difference fusion strategy isintroduced to enhance the adaptive representation of information in various regions of the source image, therebyenhancing the contrast of the fused image. The encoder and the EEM module extract features, which are thencombined in the fusion layer to create a fused picture using the decoder. Three datasets were chosen to test thealgorithmproposed in this paper. The results of the experiments demonstrate that the network effectively preservesbackground and detail information in both infrared and visible images, yielding superior outcomes in subjectiveand objective evaluations.展开更多
The isotherm is an important feature of infrared satellite cloud images (ISCI), which can directly reveal substantial information of cloud systems. The isotherm extraction of ISCI can remove the redundant information ...The isotherm is an important feature of infrared satellite cloud images (ISCI), which can directly reveal substantial information of cloud systems. The isotherm extraction of ISCI can remove the redundant information and therefore helps to compress the information of ISCI. In this paper, an isotherm extraction method is presented. The main aggregate of clouds can be segmented based on mathematical morphology. T algorithm and IP algorithm are then applied to extract the isotherms from the main aggregate of clouds. A concrete example for the extraction of isotherm based on IBM SP2 is described. The result shows that this is a high efficient algorithm. It can be used in feature extractions of infrared images for weather forecasts.展开更多
Based on an avalanche photodiode（ APD） detecting array working in Geiger mode（ GM-APD）, a high-performance infrared sensor readout integrated circuit（ ROIC） used for infrared 3D（ three-dimensional） imaging is ...Based on an avalanche photodiode（ APD） detecting array working in Geiger mode（ GM-APD）, a high-performance infrared sensor readout integrated circuit（ ROIC） used for infrared 3D（ three-dimensional） imaging is proposed. The system mainly consists of three functional modules, including active quenching circuit（ AQC）, time-to-digital converter（ TDC） circuit and other timing controller circuit. Each AQC and TDC circuit together constitutes the pixel circuit. Under the cooperation with other modules, the current signal generated by the GM-APD sensor is detected by the AQC, and the photon time-of-flight（ TOF） is measured and converted to a digital signal output to achieve a better noise suppression and a higher detection sensitivity by the TDC. The ROIC circuit is fabricated by the CSMC 0. 5 μm standard CMOS technology. The array size is 8 × 8, and the center distance of two adjacent cells is 100μm. The measurement results of the chip showthat the performance of the circuit is good, and the chip can achieve 1 ns time resolution with a 250 MHz reference clock, and the circuit can be used in the array structure of the infrared detection system or focal plane array（ FPA）.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
To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is proposed...To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is proposed.The region attention module is meant to extract the background feature map based on the distinct properties of the background feature map and the detail feature map.A multi-scale convolution attention module is suggested to enhance the communication of feature information.At the same time,the feature transformation module is introduced to learn more robust feature representations,aiming to preserve the integrity of image information.This study uses three available datasets from TNO,FLIR,and NIR to perform thorough quantitative and qualitative trials with five additional algorithms.The methods are assessed based on four indicators:information entropy(EN),standard deviation(SD),spatial frequency(SF),and average gradient(AG).Object detection experiments were done on the M3FD dataset to further verify the algorithm’s performance in comparison with five other algorithms.The algorithm’s accuracy was evaluated using the mean average precision at a threshold of 0.5(mAP@0.5)index.Comprehensive experimental findings show that CAEFusion performs well in subjective visual and objective evaluation criteria and has promising potential in downstream object detection tasks.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
To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades(WTB),this paper proposes a technique that combines morpho...To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades(WTB),this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm.First,mathematical morphology’s differential multi-scale white and black top-hat operations are applied to enhance the image.The algorithm employs entropy as the objective function to guide the iteration process of image enhancement,selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations,effectively enhancing the detail features of defect regions and improving the contrast between defects and background.Afterwards,grayscale inversion is performed on the enhanced infrared defect image to better adapt to the improved Otsu algorithm.Finally,by introducing a parameter K to adjust the calculation of inter-class variance in the Otsu method,the weight of the target pixels is increased.Combined with the adaptive iterative threshold algorithm,the threshold selection process is further fine-tuned.Experimental results show that compared to traditional Otsu algorithms and other improvements,the proposed method has significant advantages in terms of defect detection accuracy and reducing false positive rates.The average defect detection rate approaches 1,and the average Hausdorff distance decreases to 0.825,indicating strong robustness and accuracy of the method.展开更多
●AIM:To investigate a pioneering framework for the segmentation of meibomian glands(MGs),using limited annotations to reduce the workload on ophthalmologists and enhance the efficiency of clinical diagnosis.●METHODS...●AIM:To investigate a pioneering framework for the segmentation of meibomian glands(MGs),using limited annotations to reduce the workload on ophthalmologists and enhance the efficiency of clinical diagnosis.●METHODS:Totally 203 infrared meibomian images from 138 patients with dry eye disease,accompanied by corresponding annotations,were gathered for the study.A rectified scribble-supervised gland segmentation(RSSGS)model,incorporating temporal ensemble prediction,uncertainty estimation,and a transformation equivariance constraint,was introduced to address constraints imposed by limited supervision information inherent in scribble annotations.The viability and efficacy of the proposed model were assessed based on accuracy,intersection over union(IoU),and dice coefficient.●RESULTS:Using manual labels as the gold standard,RSSGS demonstrated outcomes with an accuracy of 93.54%,a dice coefficient of 78.02%,and an IoU of 64.18%.Notably,these performance metrics exceed the current weakly supervised state-of-the-art methods by 0.76%,2.06%,and 2.69%,respectively.Furthermore,despite achieving a substantial 80%reduction in annotation costs,it only lags behind fully annotated methods by 0.72%,1.51%,and 2.04%.●CONCLUSION:An innovative automatic segmentation model is developed for MGs in infrared eyelid images,using scribble annotation for training.This model maintains an exceptionally high level of segmentation accuracy while substantially reducing training costs.It holds substantial utility for calculating clinical parameters,thereby greatly enhancing the diagnostic efficiency of ophthalmologists in evaluating meibomian gland dysfunction.展开更多
In order to improve the accuracy of rolling bearing fault diagnosis when the motor is running under non-stationary conditions,an AC motor rolling bearing fault diagnosis method was proposed based on heterogeneous data...In order to improve the accuracy of rolling bearing fault diagnosis when the motor is running under non-stationary conditions,an AC motor rolling bearing fault diagnosis method was proposed based on heterogeneous data fusion of current and infrared images.Firstly,VMD was used to decompose the motor current signal and extract the low-frequency component of the bearing fault signal.On this basis,the current signal was transformed into a two-dimensional graph suitable for convolutional neural network,and the data set was classified by convolutional neural network and softmax classifier.Secondly,the infrared image was segmented and the fault features were extracted,so as to calculate the similarity with the infrared image of the fault bearing in the library,and further the sigmod classifier was used to classify the data.Finally,a decision-level fusion method was introduced to fuse the current signal with the infrared image signal diagnosis result according to the weight,and the motor bearing fault diagnosis result was obtained.Through experimental verification,the proposed fault diagnosis method could be used for the fault diagnosis of motor bearing outer ring under the condition of load variation,and the accuracy of fault diagnosis can reach 98.85%.展开更多
This review paper reports near-infrared(NIR)imaging studies using a newly-developed NIR camera,Compovision.Compovision can measure a significantly wide area of 150mm×250mm at high speed of between 2and 5s.It enab...This review paper reports near-infrared(NIR)imaging studies using a newly-developed NIR camera,Compovision.Compovision can measure a significantly wide area of 150mm×250mm at high speed of between 2and 5s.It enables a wide spectral region measurement in the 1 000~2 350nm range at 6nm intervals.We investigated the potential of Compovision in the applications to industrial problems such as the evaluation of pharmaceutical tablets and polymers.Our studies have demonstrated that NIR imaging based on Compovision can solve several issues such as long acquisition times and relatively low sensitivity of detection.NIR imaging with Compovision is strongly expected to be applied not only to pharmaceutical tablet monitoring and polymer characterization but also to various applications such as those to food products,biomedical substances and organic and inorganic materials.展开更多
Background： Despite its variety of potential applications, the wide implementation of infrared technology in cattle production faces technical, environmental and biological challenges similar to other indicators of m...Background： Despite its variety of potential applications, the wide implementation of infrared technology in cattle production faces technical, environmental and biological challenges similar to other indicators of metabolic state. Nine trials, divided into three classes （technological, environmental and biological factors） were conducted to illustrate the influence of these factors on body surface temperature assessed through infrared imaging. Results： Evaluation of technological factors indicated the following： measurements of body temperatures were strongly repeatable when taken within ]0 s; appropriateness of differing infrared camera technologies was influenced by distance to the target; and results were consistent when analysis of thermographs was compared between judges. Evaluation of environmental factors illustrated that wind and debris caused decreases in body surface temperatures without affecting metabolic rate; additionally, body surface temperature increased due to sunlight but returned to baseline values within minutes of shade exposure. Examination/investigation/exploration of animal factors demonstrated that exercise caused an increase in body surface temperature and metabolic rate. Administration of sedative and anti-sedative caused changes on body surface temperature and metabolic rate, and during late pregnancy a foetal thermal imprint was visible through abdominal infrared imaging. Conclusion： The above factors should be considered in order to standardize operational procedures for taking thermographs, thereby optimizing the use of such technology in cattle operations.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
Near infrared chemical imaging(NIR-CI)combines conventional near infrared(NIR)spectros-copy with chemical imaging,thus provides spectral and spatial information simult aneously.It could be utilized to visualize the sp...Near infrared chemical imaging(NIR-CI)combines conventional near infrared(NIR)spectros-copy with chemical imaging,thus provides spectral and spatial information simult aneously.It could be utilized to visualize the spatial distribution of the ingredients in a sample.The data acquired using NIR CI instrument are hyperspectral data cube(hypercube)containing thousands of spectra.Chemometric methodologies are necessary to transform spectral information into chemical information.Partial least squares(PLS)method was performed to extract chemical information of chlorpheniramine maleate in pharmaceutical formulations.A series of samples which consisted of different CPM concentrations(w/w)were compressed and hypercube data were measured.The spectra extracted from the hypercube were used to establish the PLS model of CPM.The results of the model were R^(2)_(val)0.981,RMSEC 0.384%,RMSECV 0.483%,RMSEP 0.631%,indicating that this model was reliable.展开更多
The application to detect ilally added drugs in dietary supplerments by near-infrared spectral imaging was studied with the focus on nifedipine,diclofenac and metformin.The method is based on near-infrared spectral im...The application to detect ilally added drugs in dietary supplerments by near-infrared spectral imaging was studied with the focus on nifedipine,diclofenac and metformin.The method is based on near-infrared spectral images correlation cofficient to detect ilally added drugs.The results comply 100%with HPLC methods test results with no false positive results.展开更多
Near infrared(NIR)fluorescence imaging guided photodynamic therapy(PDT)is a technique which has been developed in many clinical trials due to its advantage of real-time optical monitoring,specific spatiotemporal selec...Near infrared(NIR)fluorescence imaging guided photodynamic therapy(PDT)is a technique which has been developed in many clinical trials due to its advantage of real-time optical monitoring,specific spatiotemporal selectivity,and minimal invasiveness.For this,photosensitizers with NIR fluorescence emission and high^(1)O_(2)generation quantum yield are highly desirable.Herein,we designed and synthesized a"donor-acceptor"(D-A)structured semiconductor polymer(SP),which was then wrapped with an amphiphilic compound(Pluronic■F127)to prepare water-soluble nanoparticles(F-SP NPs).The obtained F-SP NPs exhibit good water solubility,excellent particle size stability,strong absorbance at deep red region,and strong NIR fluorescent emission characteristics.The maximal mass extinction coe±cient and fluorescence quantum yield of these F-SPs were calculated to be 21.7 L/(g·cm)and 6.5%,respectively.Moreover,the^(1)O_(2)quantum yield of 89%for F-SP NPs has been achieved under 635 nm laser irradiation,which is higher than Methylene Blue,Ce6,and PpIX.The outstanding properties of these F-SP NPs originate from their unique D-A molecular characteristic.This work should help guide the design of novel semiconductor polymer for NIR fluorescent imaging guided PDT applications.展开更多
Fourier transform infrared imaging(FTIRI)was used to examine the depth-dependent content variations of macromolcular components,ollagen and protooglycan(PG),in osteoarthritic and healthy cartilages.Dried 6 pmm thick s...Fourier transform infrared imaging(FTIRI)was used to examine the depth-dependent content variations of macromolcular components,ollagen and protooglycan(PG),in osteoarthritic and healthy cartilages.Dried 6 pmm thick sections of canine knee cartilages were imaged at 6.25 pμrm pixel-size in FTIRI.By analyzing the infrared(IR)images and spectra,the depth dependence of characteristic band(sugar)intensity of PG show obvious difference bet ween the cartilage sections of(OA)and bealth.The result confimns that PG content decreases in the ostcoarthritic cartilage.However,no clear change occurs to collagen,suggesting that the OA influences little on the collagen content at early stage of OA.This observation will be helpful to further understand PG loss associated with pathological conditions in OA,and demonstrates that FIIRI has the po-tential to become an important analytical tool to identify early clinical signs of tissue degna-dation,such as PG loss even collagen disruption.展开更多
Two discriminant methods,partial least squares-discriminant analysis(PLS-DA)and Fisher's discriminant analysis(FDA),were combined with Fourier transform infrared imaging(FTIRI)to differentiate healthy and osteoart...Two discriminant methods,partial least squares-discriminant analysis(PLS-DA)and Fisher's discriminant analysis(FDA),were combined with Fourier transform infrared imaging(FTIRI)to differentiate healthy and osteoarthritic articular cartilage in a canine model.Osteoarthritic cartilage had been developed for up to two years after the anterior cruciate ligament(ACL)transection in one knee.Cartilage specimens were sectioned into 10μm thickness for FTIRI.A PLS-DA model was developed after spectral pre-processing.All IR spectra extracted from FTIR images were calculated by PLS-DA with the discriminant accuracy of 90%.Prior to FDA,principal component analysis(PCA)was performed to decompose the IR spectral matrix into informative princi pal component matrices.Based on the different discriminant mechanism,the discriminant accuracy(96%)of PCA-FDA with high convenience was higher than that of PLS-DA.No healthy cartilage sample was mis assigned by these two methods.The above mentioned suggested that both integrated technologies of FTIRI-PLS-DA and,especially,FTIRI-PCA-FDA could become a promising tool for the discrimination of healthy and osteoarthritic cartilage specimen as well as the diagnosis of cartilage lesion at microscopic level.The results of the study would be helpful for better understanding the pathology of osteoarthritics.展开更多
基金financially supported by the Natural Science Foundation of Jiangsu Province(Grant No.BK20241181)the State Key Laboratory of AnalyticalChemistry for Life Science,School of Chemistry and Chemical Engineering,Nanjing University(Grant No.SKLACLS2419)。
文摘Using 2-dicyanomethylene-3-cyano-4,5,5-trimethyl-2,5-dihydrofuran(TCF)as a near-infrared fluorescent chromophore,we designed and synthesized a TCF-based fluorescent probe TCF-NS by introducing 2,4-dinitrophenyl ether as the recognized site for H_(2)S.The probe TCF-NS displayed a rapid-response fluorescent against H_(2)S with high sensitivity and selection but had no significant fluorescence response to other biothiols.Furthermore,TCF-NS was applied to sense H_(2)S in living cells successfully with minimized cytotoxicity and a large Stokes shift.
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).
文摘A novel image fusion network framework with an autonomous encoder and decoder is suggested to increase thevisual impression of fused images by improving the quality of infrared and visible light picture fusion. The networkcomprises an encoder module, fusion layer, decoder module, and edge improvementmodule. The encoder moduleutilizes an enhanced Inception module for shallow feature extraction, then combines Res2Net and Transformerto achieve deep-level co-extraction of local and global features from the original picture. An edge enhancementmodule (EEM) is created to extract significant edge features. A modal maximum difference fusion strategy isintroduced to enhance the adaptive representation of information in various regions of the source image, therebyenhancing the contrast of the fused image. The encoder and the EEM module extract features, which are thencombined in the fusion layer to create a fused picture using the decoder. Three datasets were chosen to test thealgorithmproposed in this paper. The results of the experiments demonstrate that the network effectively preservesbackground and detail information in both infrared and visible images, yielding superior outcomes in subjectiveand objective evaluations.
文摘The isotherm is an important feature of infrared satellite cloud images (ISCI), which can directly reveal substantial information of cloud systems. The isotherm extraction of ISCI can remove the redundant information and therefore helps to compress the information of ISCI. In this paper, an isotherm extraction method is presented. The main aggregate of clouds can be segmented based on mathematical morphology. T algorithm and IP algorithm are then applied to extract the isotherms from the main aggregate of clouds. A concrete example for the extraction of isotherm based on IBM SP2 is described. The result shows that this is a high efficient algorithm. It can be used in feature extractions of infrared images for weather forecasts.
基金The Natural Science Foundation of Jiangsu Province(No.BK2012559)Qing Lan Project of Jiangsu Province
文摘Based on an avalanche photodiode（ APD） detecting array working in Geiger mode（ GM-APD）, a high-performance infrared sensor readout integrated circuit（ ROIC） used for infrared 3D（ three-dimensional） imaging is proposed. The system mainly consists of three functional modules, including active quenching circuit（ AQC）, time-to-digital converter（ TDC） circuit and other timing controller circuit. Each AQC and TDC circuit together constitutes the pixel circuit. Under the cooperation with other modules, the current signal generated by the GM-APD sensor is detected by the AQC, and the photon time-of-flight（ TOF） is measured and converted to a digital signal output to achieve a better noise suppression and a higher detection sensitivity by the TDC. The ROIC circuit is fabricated by the CSMC 0. 5 μm standard CMOS technology. The array size is 8 × 8, and the center distance of two adjacent cells is 100μm. The measurement results of the chip showthat the performance of the circuit is good, and the chip can achieve 1 ns time resolution with a 250 MHz reference clock, and the circuit can be used in the array structure of the infrared detection system or focal plane array（ FPA）.
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To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is proposed.The region attention module is meant to extract the background feature map based on the distinct properties of the background feature map and the detail feature map.A multi-scale convolution attention module is suggested to enhance the communication of feature information.At the same time,the feature transformation module is introduced to learn more robust feature representations,aiming to preserve the integrity of image information.This study uses three available datasets from TNO,FLIR,and NIR to perform thorough quantitative and qualitative trials with five additional algorithms.The methods are assessed based on four indicators:information entropy(EN),standard deviation(SD),spatial frequency(SF),and average gradient(AG).Object detection experiments were done on the M3FD dataset to further verify the algorithm’s performance in comparison with five other algorithms.The algorithm’s accuracy was evaluated using the mean average precision at a threshold of 0.5(mAP@0.5)index.Comprehensive experimental findings show that CAEFusion performs well in subjective visual and objective evaluation criteria and has promising potential in downstream object detection tasks.
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.
基金supported by Natural Science Foundation of Jilin Province(YDZJ202401352ZYTS).
文摘To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades(WTB),this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm.First,mathematical morphology’s differential multi-scale white and black top-hat operations are applied to enhance the image.The algorithm employs entropy as the objective function to guide the iteration process of image enhancement,selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations,effectively enhancing the detail features of defect regions and improving the contrast between defects and background.Afterwards,grayscale inversion is performed on the enhanced infrared defect image to better adapt to the improved Otsu algorithm.Finally,by introducing a parameter K to adjust the calculation of inter-class variance in the Otsu method,the weight of the target pixels is increased.Combined with the adaptive iterative threshold algorithm,the threshold selection process is further fine-tuned.Experimental results show that compared to traditional Otsu algorithms and other improvements,the proposed method has significant advantages in terms of defect detection accuracy and reducing false positive rates.The average defect detection rate approaches 1,and the average Hausdorff distance decreases to 0.825,indicating strong robustness and accuracy of the method.
基金Supported by Natural Science Foundation of Fujian Province(No.2020J011084)Fujian Province Technology and Economy Integration Service Platform(No.2023XRH001)Fuzhou-Xiamen-Quanzhou National Independent Innovation Demonstration Zone Collaborative Innovation Platform(No.2022FX5)。
文摘●AIM:To investigate a pioneering framework for the segmentation of meibomian glands(MGs),using limited annotations to reduce the workload on ophthalmologists and enhance the efficiency of clinical diagnosis.●METHODS:Totally 203 infrared meibomian images from 138 patients with dry eye disease,accompanied by corresponding annotations,were gathered for the study.A rectified scribble-supervised gland segmentation(RSSGS)model,incorporating temporal ensemble prediction,uncertainty estimation,and a transformation equivariance constraint,was introduced to address constraints imposed by limited supervision information inherent in scribble annotations.The viability and efficacy of the proposed model were assessed based on accuracy,intersection over union(IoU),and dice coefficient.●RESULTS:Using manual labels as the gold standard,RSSGS demonstrated outcomes with an accuracy of 93.54%,a dice coefficient of 78.02%,and an IoU of 64.18%.Notably,these performance metrics exceed the current weakly supervised state-of-the-art methods by 0.76%,2.06%,and 2.69%,respectively.Furthermore,despite achieving a substantial 80%reduction in annotation costs,it only lags behind fully annotated methods by 0.72%,1.51%,and 2.04%.●CONCLUSION:An innovative automatic segmentation model is developed for MGs in infrared eyelid images,using scribble annotation for training.This model maintains an exceptionally high level of segmentation accuracy while substantially reducing training costs.It holds substantial utility for calculating clinical parameters,thereby greatly enhancing the diagnostic efficiency of ophthalmologists in evaluating meibomian gland dysfunction.
基金supported by National Natural Science Foundation of China(No.61903291)Shaanxi Province Key R&D Program(No.2022GY-134)。
文摘In order to improve the accuracy of rolling bearing fault diagnosis when the motor is running under non-stationary conditions,an AC motor rolling bearing fault diagnosis method was proposed based on heterogeneous data fusion of current and infrared images.Firstly,VMD was used to decompose the motor current signal and extract the low-frequency component of the bearing fault signal.On this basis,the current signal was transformed into a two-dimensional graph suitable for convolutional neural network,and the data set was classified by convolutional neural network and softmax classifier.Secondly,the infrared image was segmented and the fault features were extracted,so as to calculate the similarity with the infrared image of the fault bearing in the library,and further the sigmod classifier was used to classify the data.Finally,a decision-level fusion method was introduced to fuse the current signal with the infrared image signal diagnosis result according to the weight,and the motor bearing fault diagnosis result was obtained.Through experimental verification,the proposed fault diagnosis method could be used for the fault diagnosis of motor bearing outer ring under the condition of load variation,and the accuracy of fault diagnosis can reach 98.85%.
文摘This review paper reports near-infrared(NIR)imaging studies using a newly-developed NIR camera,Compovision.Compovision can measure a significantly wide area of 150mm×250mm at high speed of between 2and 5s.It enables a wide spectral region measurement in the 1 000~2 350nm range at 6nm intervals.We investigated the potential of Compovision in the applications to industrial problems such as the evaluation of pharmaceutical tablets and polymers.Our studies have demonstrated that NIR imaging based on Compovision can solve several issues such as long acquisition times and relatively low sensitivity of detection.NIR imaging with Compovision is strongly expected to be applied not only to pharmaceutical tablet monitoring and polymer characterization but also to various applications such as those to food products,biomedical substances and organic and inorganic materials.
基金the Beef Producers of Ontario,Ontario Ministry of Agriculture and Rural Affairs,Beef Cattle Research Council and Agri-Food Canada for financial support
文摘Background： Despite its variety of potential applications, the wide implementation of infrared technology in cattle production faces technical, environmental and biological challenges similar to other indicators of metabolic state. Nine trials, divided into three classes （technological, environmental and biological factors） were conducted to illustrate the influence of these factors on body surface temperature assessed through infrared imaging. Results： Evaluation of technological factors indicated the following： measurements of body temperatures were strongly repeatable when taken within ]0 s; appropriateness of differing infrared camera technologies was influenced by distance to the target; and results were consistent when analysis of thermographs was compared between judges. Evaluation of environmental factors illustrated that wind and debris caused decreases in body surface temperatures without affecting metabolic rate; additionally, body surface temperature increased due to sunlight but returned to baseline values within minutes of shade exposure. Examination/investigation/exploration of animal factors demonstrated that exercise caused an increase in body surface temperature and metabolic rate. Administration of sedative and anti-sedative caused changes on body surface temperature and metabolic rate, and during late pregnancy a foetal thermal imprint was visible through abdominal infrared imaging. Conclusion： The above factors should be considered in order to standardize operational procedures for taking thermographs, thereby optimizing the use of such technology in cattle operations.
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 from Beijing Municipal Government for the university a±liated with the Party Central Committee(Prof.Shi)National Natural Science Foundation of China(81303218)+1 种基金Doctoral Fund of Ministry of Education of China(20130013120006)Special Fund of Beijing University of Chinese Medicine(Manfei Xu).
文摘Near infrared chemical imaging(NIR-CI)combines conventional near infrared(NIR)spectros-copy with chemical imaging,thus provides spectral and spatial information simult aneously.It could be utilized to visualize the spatial distribution of the ingredients in a sample.The data acquired using NIR CI instrument are hyperspectral data cube(hypercube)containing thousands of spectra.Chemometric methodologies are necessary to transform spectral information into chemical information.Partial least squares(PLS)method was performed to extract chemical information of chlorpheniramine maleate in pharmaceutical formulations.A series of samples which consisted of different CPM concentrations(w/w)were compressed and hypercube data were measured.The spectra extracted from the hypercube were used to establish the PLS model of CPM.The results of the model were R^(2)_(val)0.981,RMSEC 0.384%,RMSECV 0.483%,RMSEP 0.631%,indicating that this model was reliable.
基金support of National Science and Technology Support Program (2012BAK08B02)Beijing Institute for Drug Control and Jiangsu Institute for Food and Drug Control for their generous providing of dietary supplements samples.
文摘The application to detect ilally added drugs in dietary supplerments by near-infrared spectral imaging was studied with the focus on nifedipine,diclofenac and metformin.The method is based on near-infrared spectral images correlation cofficient to detect ilally added drugs.The results comply 100%with HPLC methods test results with no false positive results.
基金This work was supported by National Natural Science Foundation of China(Nos.61805287 and 62175262)The Open Fund of the State Key Laboratory of Luminescent Materials and Devices(South China University of Technology,No.2021-skllmd-10)+1 种基金The Open Sharing Fund for Large-scale Instruments and Equipment of Central South University(CSUZC202218),Fundamental Research Funds for the Central South Universities(Nos.2020CX021,2020zzts387,and 2020zzts404)Key R&D plan of Hunan Province(No.2022SK2101).
文摘Near infrared(NIR)fluorescence imaging guided photodynamic therapy(PDT)is a technique which has been developed in many clinical trials due to its advantage of real-time optical monitoring,specific spatiotemporal selectivity,and minimal invasiveness.For this,photosensitizers with NIR fluorescence emission and high^(1)O_(2)generation quantum yield are highly desirable.Herein,we designed and synthesized a"donor-acceptor"(D-A)structured semiconductor polymer(SP),which was then wrapped with an amphiphilic compound(Pluronic■F127)to prepare water-soluble nanoparticles(F-SP NPs).The obtained F-SP NPs exhibit good water solubility,excellent particle size stability,strong absorbance at deep red region,and strong NIR fluorescent emission characteristics.The maximal mass extinction coe±cient and fluorescence quantum yield of these F-SPs were calculated to be 21.7 L/(g·cm)and 6.5%,respectively.Moreover,the^(1)O_(2)quantum yield of 89%for F-SP NPs has been achieved under 635 nm laser irradiation,which is higher than Methylene Blue,Ce6,and PpIX.The outstanding properties of these F-SP NPs originate from their unique D-A molecular characteristic.This work should help guide the design of novel semiconductor polymer for NIR fluorescent imaging guided PDT applications.
基金The authors are grateful to the National Institutes of Health in U.S.A.for the R01 grants(AR 045172,AR 052353)to Yang Xia.
文摘Fourier transform infrared imaging(FTIRI)was used to examine the depth-dependent content variations of macromolcular components,ollagen and protooglycan(PG),in osteoarthritic and healthy cartilages.Dried 6 pmm thick sections of canine knee cartilages were imaged at 6.25 pμrm pixel-size in FTIRI.By analyzing the infrared(IR)images and spectra,the depth dependence of characteristic band(sugar)intensity of PG show obvious difference bet ween the cartilage sections of(OA)and bealth.The result confimns that PG content decreases in the ostcoarthritic cartilage.However,no clear change occurs to collagen,suggesting that the OA influences little on the collagen content at early stage of OA.This observation will be helpful to further understand PG loss associated with pathological conditions in OA,and demonstrates that FIIRI has the po-tential to become an important analytical tool to identify early clinical signs of tissue degna-dation,such as PG loss even collagen disruption.
基金the National Natural Science Foundation of China for the grant of 61378087Natural Science Foundation of Jiangsu Province(BK20151478)+1 种基金Zhi-Hua Mao is grateful to the Open Funds for Graduate Innovation Lab of Nanjing University of Aeronautics and Astronautics(kfjj20150309)and Fundamental Research Funds for the Central Universities.The raw data acquisition in FTIRI was mostly carried out in the lab of Professor Yang Xia at Oakland University(Rochester,Michigan,USA).Professor Xia was supported by an NIH grant R01-AR052353 during the time of the data acquisition.
文摘Two discriminant methods,partial least squares-discriminant analysis(PLS-DA)and Fisher's discriminant analysis(FDA),were combined with Fourier transform infrared imaging(FTIRI)to differentiate healthy and osteoarthritic articular cartilage in a canine model.Osteoarthritic cartilage had been developed for up to two years after the anterior cruciate ligament(ACL)transection in one knee.Cartilage specimens were sectioned into 10μm thickness for FTIRI.A PLS-DA model was developed after spectral pre-processing.All IR spectra extracted from FTIR images were calculated by PLS-DA with the discriminant accuracy of 90%.Prior to FDA,principal component analysis(PCA)was performed to decompose the IR spectral matrix into informative princi pal component matrices.Based on the different discriminant mechanism,the discriminant accuracy(96%)of PCA-FDA with high convenience was higher than that of PLS-DA.No healthy cartilage sample was mis assigned by these two methods.The above mentioned suggested that both integrated technologies of FTIRI-PLS-DA and,especially,FTIRI-PCA-FDA could become a promising tool for the discrimination of healthy and osteoarthritic cartilage specimen as well as the diagnosis of cartilage lesion at microscopic level.The results of the study would be helpful for better understanding the pathology of osteoarthritics.
