Fusion SST from Infrared and Microwave Measurement of FY-3D Meteorological Satellite

Sea surface temperature(SST)is one of the important parameters of global ocean and climate research,which can be retrieved by satellite infrared and passive microwave remote sensing instruments.While satellite infrared SST offers high spatial resolution,it is limited by cloud cover.On the other hand,passive microwave SST provides all-weather observation but suffers from poor spatial resolution and susceptibility to environmental factors such as rainfall,coastal effects,and high wind speeds.To achieve high-precision,comprehensive,and high-resolution SST data,it is essential to fuse infrared and microwave SST measurements.In this study,data from the Fengyun-3D(FY-3D)medium resolution spectral imager II(MERSI-II)SST and microwave imager(MWRI)SST were fused.Firstly,the accuracy of both MERSIII SST and MWRI SST was verified,and the latter was bilinearly interpolated to match the 5km resolution grid of MERSI SST.After pretreatment and quality control of MERSI SST and MWRI SST,a Piece-Wise Regression method was employed to correct biases in MWRI SST.Subsequently,SST data were selected based on spatial resolution and accuracy within a 3-day window of the analysis date.Finally,an optimal interpolation method was applied to fuse the FY-3D MERSI-II SST and MWRI SST.The results demonstrated a significant improvement in spatial coverage compared to MERSI-II SST and MWRI SST.Furthermore,the fusion SST retained true spatial distribution details and exhibited an accuracy of–0.12±0.74℃compared to OSTIA SST.This study has improved the accuracy of FY satellite fusion SST products in China.

Infrared and Visible Image Fusion Based on Res2Net-Transformer Automatic Encoding and Decoding

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.

Efficient Electromagnetic Wave Absorption and Thermal Infrared Stealth in PVTMS@MWCNT Nano‑Aerogel via Abundant Nano‑Sized Cavities and Attenuation Interfaces

Pre-polymerized vinyl trimethoxy silane(PVTMS)@MWCNT nano-aerogel system was constructed via radical polymerization,sol-gel transition and supercritical CO_(2)drying.The fabricated organic-inorganic hybrid PVTMS@MWCNT aerogel structure shows nano-pore size(30-40 nm),high specific surface area(559 m^(2)g^(−1)),high void fraction(91.7%)and enhanced mechanical property:(1)the nano-pore size is beneficial for efficiently blocking thermal conduction and thermal convection via Knudsen effect(beneficial for infrared(IR)stealth);(2)the heterogeneous interface was beneficial for IR reflection(beneficial for IR stealth)and MWCNT polarization loss(beneficial for electromagnetic wave(EMW)attenuation);(3)the high void fraction was beneficial for enhancing thermal insulation(beneficial for IR stealth)and EMW impedance match(beneficial for EMW attenuation).Guided by the above theoretical design strategy,PVTMS@MWCNT nano-aerogel shows superior EMW absorption property(cover all Ku-band)and thermal IR stealth property(ΔT reached 60.7℃).Followed by a facial combination of the above nano-aerogel with graphene film of high electrical conductivity,an extremely high electromagnetic interference shielding material(66.5 dB,2.06 mm thickness)with superior absorption performance of an average absorption-to-reflection(A/R)coefficient ratio of 25.4 and a low reflection bandwidth of 4.1 GHz(A/R ratio more than 10)was experimentally obtained in this work.

CAEFusion: A New Convolutional Autoencoder-Based Infrared and Visible Light Image Fusion Algorithm

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.

Lightweight Dual‑Functional Segregated Nanocomposite Foams for Integrated Infrared Stealth and Absorption‑Dominant Electromagnetic Interference Shielding

Lightweight infrared stealth and absorption-dominant electromagnetic interference(EMI)shielding materials are highly desirable in areas of aerospace,weapons,military and wearable electronics.Herein,lightweight and high-efficiency dual-functional segregated nanocomposite foams with microcellular structures are developed for integrated infrared stealth and absorption-dominant EMI shielding via the efficient and scalable supercritical CO_(2)(SC-CO_(2))foaming combined with hydrogen bonding assembly and compression molding strategy.The obtained lightweight segregated nanocomposite foams exhibit superior infrared stealth performances benefitting from the synergistic effect of highly effective thermal insulation and low infrared emissivity,and outstanding absorption-dominant EMI shielding performances attributed to the synchronous construction of microcellular structures and segregated structures.Particularly,the segregated nanocomposite foams present a large radiation temperature reduction of 70.2℃ at the object temperature of 100℃,and a significantly improved EM wave absorptivity/reflectivity(A/R)ratio of 2.15 at an ultralow Ti_(3)C_(2)T_(x) content of 1.7 vol%.Moreover,the segregated nanocomposite foams exhibit outstanding working reliability and stability upon dynamic compression cycles.The results demonstrate that the lightweight and high-efficiency dual-functional segregated nanocomposite foams have excellent potentials for infrared stealth and absorption-dominant EMI shielding applications in aerospace,weapons,military and wearable electronics.

Infrared microspectroscopy beamline BL06B at SSRF

The infrared microspectroscopy beamline(BL06B) is a phase Ⅱ beamline project at the Shanghai Synchrotron Radiation Facility(SSRF). The construction and optical alignment of BL06B were completed by the end of 2020. By 2021, it became accessible to users. The synchrotron radiation infrared(SRIR) source included edge radiation(ER) and bending magnet radiation(BMR). The extracted angles in the horizontal and vertical directions were 40 and 20 mrad, respectively. The photon flux, spectral resolution, and focused spot size were measured at the BL06B endstation, and the experimental results were consistent with theoretical calculations. SRIR light has a small divergence angle, high brightness, and a wide wavelength range. As a source of IR microscopy, it can easily focus on a diffraction-limited spatial resolution with a high signal-to-noise ratio(SNR). The BL06B endstation can be applied in a wide range of research fields, including materials, chemistry, biology, geophysics, and pharmacology.

ESIT 2024: Gathering of Global Minds to Hangzhou for Cutting-Edge Infrared and Terahertz Innovation

The third Earth&Space:from Infrared to Terahertz International Conference(ESIT 2024)successfully took place in Hangzhou,China,from September 20 to 22,2024.Co-hosted by the Shanghai Institute of Technical Physics,Chinese'Academy of Sciences(SITP)along with five prestigious institutions,the conference provided a premier platform for international collaboration on cutting-edge developments in infrared,terahertz,and space exploration technologies.

Erratum to:Deriving Temporal and Vertical Distributions of Methane in Xianghe Using Ground-based Fourier Transform Infrared and Gas-analyzer

“Diurnal variation of CH4 at the surface from spring to winter.The time units are in local time(+8 h UTC).The error bar is 1σfor all the observed hourly mean data within that season at that local time.”in the caption of Fig.8 on Page 604 should be“Diurnal variation of CH4 at the surface from spring to winter.The time units are in UTC.The error bar is 1σfor all the observed hourly mean data within that season at that local time.”

Multifunctional MXene/Carbon Nanotube Janus Film for Electromagnetic Shielding and Infrared Shielding/Detection in Harsh Environments

Multifunctional,flexible,and robust thin films capable of operating in demanding harsh temperature environments are crucial for various cutting-edge applications.This study presents a multifunctional Janus film integrating highly-crystalline Ti_(3)C_(2)T_(x) MXene and mechanically-robust carbon nanotube(CNT)film through strong hydrogen bonding.The hybrid film not only exhibits high electrical conductivity(4250 S cm^(-1)),but also demonstrates robust mechanical strength and durability in both extremely low and high temperature environments,showing exceptional resistance to thermal shock.This hybrid Janus film of 15μm thickness reveals remarkable multifunctionality,including efficient electromagnetic shielding effectiveness of 72 dB in X band frequency range,excellent infrared(IR)shielding capability with an average emissivity of 0.09(a minimal value of 0.02),superior thermal camouflage performance over a wide temperature range(−1 to 300℃)achieving a notable reduction in the radiated temperature by 243℃ against a background temperature of 300℃,and outstanding IR detection capability characterized by a 44%increase in resistance when exposed to 250 W IR radiation.This multifunctional MXene/CNT Janus film offers a feasible solution for electromagnetic shielding and IR shielding/detection under challenging conditions.

Intense Mid-Infrared Laser Pulse Generated via Flying-Mirror Red-Shifting in Near-Critical-Density Plasmas

Relativistic femtosecond mid-infrared pulses can be generated efficiently by laser interaction with near-criticaldensity plasmas.It is found theoretically and numerically that the radiation pressure of a circularly polarized laser pulse first compresses the plasma electrons to form a dense flying mirror with a relativistic high speed.The pulse reflected by the mirror is red-shifted to the mid-infrared range.Full three-dimensional simulations demonstrate that the central wavelength of the mid-infrared pulse is tunable from 3µm to 14µm,and the laser energy conversion efficiency can reach as high as 13%.With a 0.5–10 PW incident laser pulse,the generated mid-infrared pulse reaches a peak power of 10–180 TW,which is interesting for various applications in ultrafast and high-field sciences.

Rice Variety Classification Based on Optimized Near-Infrared Spectral Classification Model

Accurate classification of rice variety is essential to ensure the brand value of high-quality rice products.Considering the impact of sample state on modeling optimization algorithms,rice samples after grinding and sealing were selected.To enhance the accuracy of rice variety classification,we introduced a spectral characteristic wavelength selection method based on adaptive sliding window permutation entropy(ASW-PE).

New Vacuum Solar Telescope Achieves Narrowband Infrared Solar Imaging Observation at He I 10830 A

The near-infrared imaging channel constitutes a crucial component of the multichannel high-resolution imaging system of the New Vacuum Solar Telescope(NVST). We have successfully achieved high-resolution, narrowband imaging of the chromosphere using He I 10830 A triplet within this channel, which significantly enhances the imaging observation capabilities of NVST. This paper provides a concise overview of the optical system associated with the near-infrared imaging channel, detailing data processing procedures and presenting several observed images. Leveraging a high-resolution image reconstruction algorithm, we were able to generate a narrowband image near the diffraction limit at 10830 A with a temporal resolution of less than 10 s.

Long wavelength infrared metalens fabricated by photolithography

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.

Extraction of the key infrared radiation temperature features concerning stress and crack evolution of loaded rocks

The infrared radiation temperature(IRT)variation concerning stress and crack evolution of rocks is a critical focus in rock mechanics domain and engineering disaster warning.In this paper,a methodology to extract the key IRT features related to stress and crack evolution of loaded rocks is proposed.Specifically,the wavelet denoising and reconstruction in thermal image sequence(WDRTIS)method is employed to eliminate temporal noise in thermal image sequences.Subsequently,the adaptive partition temperature drift correction(APTDC)method is introduced to alleviate temperature drift.On this basis,the spatial noise correction method based on threshold segmentation and adaptive median filtering(OTSU-AMF)is proposed to extract the key IRT features associated with microcracks of loaded rocks.Following temperature drift correction,IRT provides an estimation of the thermoelastic factor in rocks,typically around 5.29×10^(-5) MPa^(-1) for sandstones.Results reveal that the high-temperature concentrated region in cumulative thermal images of crack evolution(TICE)can elucidate the spatiotemporal evolution of localized damage.Additionally,heat dissipation of crack evolution(HDCE)acquired from TICE quantifies the progressive failure process of rocks.The proposed methodology enhances the reliability of IRT monitoring results and provides an innovative approach for conducting research in rock mechanics and monitoring engineering disasters.

Advancing automated pupillometry:a practical deep learning model utilizing infrared pupil images

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.

Infrared microthermometry of fluid inclusion in sphalerite:A case study of the Xinqiao deposit in the Middle-Lower Yangtze metallogenic belt

Infrared microthermometry allows direct measurement of fluid inclusions hosted in opaque ore minerals and can provide direct constraints on the evolution of ore-forming fluids.This study presents infrared microthermometry of spherite-hosted fluid inclusions from the Xinqiao deposit in the Middle-Lower Yangtze Metallogenic Belt and sheds new light on the ore genesis of the deposit.Considering that infrared light may lead to non-negligible temperature deviations during microthermometry,some tests were first conducted to ensure the accuracy of the microthermometric measurements.The measurement results indicated that using the lowest light intensity of the microscope and inserting an optical filter were effective in minimizing the possible temperature deviations of infrared microthermometry.All sphalerite-hosted fluid inclusions from the Xinqiao deposit were aqueous.They show homogenization temperature ranging from~200 to 350℃,but have two separate salinity groups(1.0 wt%-10 wt%and 15.1 wt%-19.2 wt%NaCl equivalent).The low-salinity group represents sedimentary exhalative(SEDEX)-associated fluids,whereas the high-salinity group results from modification by later magmatic hydrothermal fluids.Combined with published fluid inclusion data,the four-stage fluid evolution of the Xinqiao deposit was depicted.Furthermore,our data suggest that the Xinqiao deposit was formed by twostage metallogenic events including SEDEX and magmatic-hydrothermal mineralization.

Ultra-soft Desorption Assisted Mass Spectrometry using Picosecond Infrared Laser for the Detection of lons in the Liquid Surface

To identify the species in liquid surface using mass spectrometry,we must eliminate or reduce interferences during the vaporization or desorption of the species from the liquid surface.It is much more challenging to isolate the ionic,larger species from the liquid surface,because of the frangible structures and the higher solvation energies of those species.Here we demonstrate a new mass spectrometry in which the ionic species at the liquid surface can be desorbed with ultrasoft infrared picosecond laser pulses while the liquid surface is not breached.This laser desorption assisted mass spectrometry is not only a powerful tool to detect the fragile species but also promising to investigate vibrational energy transfer dynamics in the liquid surface.

Adversarial Defense Technology for Small Infrared Targets

With the rapid development of deep learning-based detection algorithms,deep learning is widely used in the field of infrared small target detection.However,well-designed adversarial samples can fool human visual perception,directly causing a serious decline in the detection quality of the recognition model.In this paper,an adversarial defense technology for small infrared targets is proposed to improve model robustness.The adversarial samples with strong migration can not only improve the generalization of defense technology,but also save the training cost.Therefore,this study adopts the concept of maximizing multidimensional feature distortion,applying noise to clean samples to serve as subsequent training samples.On this basis,this study proposes an inverse perturbation elimination method based on Generative Adversarial Networks(GAN)to realize the adversarial defense,and design the generator and discriminator for infrared small targets,aiming to make both of them compete with each other to continuously improve the performance of the model,find out the commonalities and differences between the adversarial samples and the original samples.Through experimental verification,our defense algorithm is not only able to cope with multiple attacks but also performs well on different recognition models compared to commonly used defense algorithms,making it a plug-and-play efficient adversarial defense technique.

Application of near-infrared spectroscopy for fast germplasm analysis and classification in multi-environment using intact-seed peanut(Arachis hypogaea L.)

Peanut is a worldwide oilseed crop and the need to assess germplasm in a non-destructive manner is important for seed nutritional breeding.In this study,Near Infrared Spectroscopy(NIRS)was applied to rapidly assess germplasm variability from whole seed of 699 samples,field-collected and assembled in four genetic and environmentbased sets:one set of 300 varieties of a core-collection and three sets of 133 genotypes of an interspecific population,evaluated in three environments in a large spatial scale of two countries,Mbalmayo and Bafia in Cameroon and Nioro in Senegal,under rainfed conditions.NIR elemental spectra were gathered on six subsets of seeds of each sample,after three rotation scans,with a spectral resolution of 16 cm-1over the spectral range of867 nm to 2530 nm.Spectra were then processed by principal component analysis(PCA)coupled with Partial least squares-discriminant analysis(PLS-DA).As results,a huge variability was found between varieties and genotypes for all NIR wavelength within and between environments.The magnitude of genetic variation was particularly observed at 11 relevant wavelengths such as 1723 nm,usually related to oil content and fatty acid composition.PCA yielded the most chemical attributes in three significant PCs(i.e.,eigenvalues>10),which together captured 93%of the total variation,revealing genetic and environment structure of varieties and genotypes into four clusters,corresponding to the four samples sets.The pattern of genetic variability of the interspecific population covers,remarkably half of spectrum of the core-collection,turning out to be the largest.Interestingly,a PLS-DA model was developed and a strong accuracy of 99.6%was achieved for the four sets,aiming to classify each seed sample according to environment origin.The confusion matrix achieved for the two sets of Bafia and Nioro showed 100%of instances classified correctly with 100%at both sensitivity and specificity,confirming that their seed quality was different from each other and all other samples.Overall,NIRS chemometrics is useful to assess and distinguish seeds from different environments and highlights the value of the interspecific population and core-collection,as a source of nutritional diversity,to support the breeding efforts.

Failure mechanism and infrared radiation characteristic of hard siltstone induced by stratification effect

The deformation in sedimentary rock induced by train loads has potential threat to the safe operation of tunnels. This study investigated the influence of stratification structure on the infrared radiation and temporal damage mechanism of hard siltstone. The uniaxial compression tests, coupled with acoustic emission(AE) and infrared radiation temperature(IRT) were conducted on siltstones with different stratification effects. The results revealed that the stratigraphic structure significantly affects the stress-strain response and strength degradation characteristics. The mechanical parameters exhibit anisotropy characteristics, and the stratification effect exhibits a negative correlation with the cracking stress and peak stress. The failure modes caused by the stratification effect show remarkable anisotropic features, including splitting failure(Ⅰ: 0°-22.50°, Ⅱ: 90°), composite failure(45°), and shearing failure(67.50°). The AE temporal sequences demonstrate a stepwise response characteristic to the loading stress level. The AE intensity indicates that the stress sensitivity of shearing failure and composite failure is generally greater than that of splitting failure. The IRT field has spatiotemporal migration and progressive dissimilation with stress loading and its dissimilation degree increases under higher stress levels. The stronger the stratification effect, the greater the dissimilation degree of the IRT field. The abnormal characteristic points of average infrared radiation temperature(AIRT) variance at local stress drop and peak stress can be used as early and late precursors to identify fracture instability. Theoretical analysis shows that the competitive relationship between compaction strengthening and fracturing damage intensifies the dissimilation of the infrared thermal field for an increasing stress level. The present study provides a theoretical reference for disaster warnings in hard sedimentary rock mass.