The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method f...The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.展开更多
The goal of infrared and visible image fusion(IVIF)is to integrate the unique advantages of both modalities to achieve a more comprehensive understanding of a scene.However,existing methods struggle to effectively han...The goal of infrared and visible image fusion(IVIF)is to integrate the unique advantages of both modalities to achieve a more comprehensive understanding of a scene.However,existing methods struggle to effectively handle modal disparities,resulting in visual degradation of the details and prominent targets of the fused images.To address these challenges,we introduce Prompt Fusion,a prompt-based approach that harmoniously combines multi-modality images under the guidance of semantic prompts.Firstly,to better characterize the features of different modalities,a contourlet autoencoder is designed to separate and extract the high-/low-frequency components of different modalities,thereby improving the extraction of fine details and textures.We also introduce a prompt learning mechanism using positive and negative prompts,leveraging Vision-Language Models to improve the fusion model's understanding and identification of targets in multi-modality images,leading to improved performance in downstream tasks.Furthermore,we employ bi-level asymptotic convergence optimization.This approach simplifies the intricate non-singleton non-convex bi-level problem into a series of convergent and differentiable single optimization problems that can be effectively resolved through gradient descent.Our approach advances the state-of-the-art,delivering superior fusion quality and boosting the performance of related downstream tasks.Project page:https://github.com/hey-it-s-me/PromptFusion.展开更多
Infrared and visible image fusion technology integrates the thermal radiation information of infrared images with the texture details of visible images to generate more informative fused images.However,existing method...Infrared and visible image fusion technology integrates the thermal radiation information of infrared images with the texture details of visible images to generate more informative fused images.However,existing methods often fail to distinguish salient objects from background regions,leading to detail suppression in salient regions due to global fusion strategies.This study presents a mask-guided latent low-rank representation fusion method to address this issue.First,the GrabCut algorithm is employed to extract a saliency mask,distinguishing salient regions from background regions.Then,latent low-rank representation(LatLRR)is applied to extract deep image features,enhancing key information extraction.In the fusion stage,a weighted fusion strategy strengthens infrared thermal information and visible texture details in salient regions,while an average fusion strategy improves background smoothness and stability.Experimental results on the TNO dataset demonstrate that the proposed method achieves superior performance in SPI,MI,Qabf,PSNR,and EN metrics,effectively preserving salient target details while maintaining balanced background information.Compared to state-of-the-art fusion methods,our approach achieves more stable and visually consistent fusion results.The fusion code is available on GitHub at:https://github.com/joyzhen1/Image(accessed on 15 January 2025).展开更多
Mixed-phase clouds(MPCs)involve complex microphysical and dynamical processes of cloud formation and dissipation,which are crucial for numerical weather prediction and cloud-climate feedback.However,satellite remote s...Mixed-phase clouds(MPCs)involve complex microphysical and dynamical processes of cloud formation and dissipation,which are crucial for numerical weather prediction and cloud-climate feedback.However,satellite remote sensing of MPC properties is still challenging,and there is seldom MPC result inferred from passive spectral observations.This study examines the spectral characteristics of MPCs in the shortwave-infrared(SWIR)channels over the wavelength of 0.4–2.5μm,and evaluates the potential of current operational satellite spectroradiometer channels for MPC retrievals.With optical properties of MPCs based on the assumption of uniform mixing of both ice and liquid water particles,the effects of MPC ice optical thickness fraction(IOTF)and effective radius on associated optical properties are analyzed.As expected,results indicate that the MPC optical properties show features for ice and liquid water clouds,and their spectral variations show noticeable differences from those for homogeneous cases.A radiative transfer method is employed to examine the sensitivity of SWIR channels to given MPC cloud water path(CWP)and IOTF.MPCs have unique signal characteristics in the SWIR spectrum.The 0.87-μm channel is most sensitive to CWP.Meanwhile,the 1.61-and 2.13-μm channels are more sensitive to water-dominated MPCs(IOTF approaching 0),and the 2.25-μm channel is sensitive to both water-dominated and ice-dominated MPCs(IOTF approaching 1).Such spectral differences are potentially possible to be used to infer MPC properties based on radiometer observations,which will be investigated in future studies.展开更多
Infrared and visible light image fusion technology integrates feature information from two different modalities into a fused image to obtain more comprehensive information.However,in low-light scenarios,the illuminati...Infrared and visible light image fusion technology integrates feature information from two different modalities into a fused image to obtain more comprehensive information.However,in low-light scenarios,the illumination degradation of visible light images makes it difficult for existing fusion methods to extract texture detail information from the scene.At this time,relying solely on the target saliency information provided by infrared images is far from sufficient.To address this challenge,this paper proposes a lightweight infrared and visible light image fusion method based on low-light enhancement,named LLE-Fuse.The method is based on the improvement of the MobileOne Block,using the Edge-MobileOne Block embedded with the Sobel operator to perform feature extraction and downsampling on the source images.The intermediate features at different scales obtained are then fused by a cross-modal attention fusion module.In addition,the Contrast Limited Adaptive Histogram Equalization(CLAHE)algorithm is used for image enhancement of both infrared and visible light images,guiding the network model to learn low-light enhancement capabilities through enhancement loss.Upon completion of network training,the Edge-MobileOne Block is optimized into a direct connection structure similar to MobileNetV1 through structural reparameterization,effectively reducing computational resource consumption.Finally,after extensive experimental comparisons,our method achieved improvements of 4.6%,40.5%,156.9%,9.2%,and 98.6%in the evaluation metrics Standard Deviation(SD),Visual Information Fidelity(VIF),Entropy(EN),and Spatial Frequency(SF),respectively,compared to the best results of the compared algorithms,while only being 1.5 ms/it slower in computation speed than the fastest method.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
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
This article proposes a novel method to fuse infrared and visible light images based on region segmentation. Region segmen-tation is used to determine important regions and background information in the input image. T...This article proposes a novel method to fuse infrared and visible light images based on region segmentation. Region segmen-tation is used to determine important regions and background information in the input image. The non-subsampled contourlet transform (NSCT) provides a flexible multiresolution,local and directional image expansion,and also a sparse representation for two-dimensional (2-D) piecewise smooth signal building images,and then different fusion rules are applied to fuse the NSCT coefficients fo...展开更多
Traditional stealth materials do not fulfill the requirements of high absorption for radar waves and low emissivity for infrared waves.Furthermore,they can be detected by various technologies,considerably threatening ...Traditional stealth materials do not fulfill the requirements of high absorption for radar waves and low emissivity for infrared waves.Furthermore,they can be detected by various technologies,considerably threatening weapon safety.Therefore,a stealth material compatible with radar and infrared was designed based on the photonic bandgap characteristics of photonic crystals.The radar stealth lay-er(bottom layer)is a composite of carbonyl iron/silicon dioxide/epoxy resin,and the infrared stealth layer(top layer)is a 1D photonic crystal with alternately and periodically stacked germanium and silicon nitride.Through composition optimization and structural adjust-ment,the effective absorption bandwidth of the compatible stealth material with a reflection loss of less than-10 dB has reached 4.95 GHz.The average infrared emissivity of the proposed design is 0.1063,indicating good stealth performance.The theoretical analysis proves that photonic crystals with this structural design can produce infrared waves within the photonic bandgap,achieving high radar wave transmittance and low infrared emissivity.Infrared stealth is achieved without affecting the absorption performance of the radar stealth layer,and the conflict between radar and infrared stealth performance is resolved.This work aims to promote the application of photonic crystals in compatible stealth materials and the development of stealth technology and to provide a design and theoretical found-ation for related experiments and research.展开更多
The removal of ammonia nitrogen(NH_(4)^(+)-N)and bacteria from aquaculture wastewater holds paramount ecological and production significance.In this study,Pt/RuO_(2)/g-C_(3)N_(4)photocatalysts were prepared by deposit...The removal of ammonia nitrogen(NH_(4)^(+)-N)and bacteria from aquaculture wastewater holds paramount ecological and production significance.In this study,Pt/RuO_(2)/g-C_(3)N_(4)photocatalysts were prepared by depositing Pt and RuO_(2)particles onto g-C_(3)N_(4).The physicochemical properties of photocatalysts were explored by X-ray photoelectron spectroscopy(XPS),scanning electron microscopy(SEM),X-ray diffraction(XRD),and UV–vis diffuse reflectance spectrometer(UV–vis DRS).The photocatalysts were then applied to the removal of both NH_(4)^(+)-N and bacteria from simulated mariculture wastewater.The results clarified that the removals of both NH_(4)^(+)-N and bacteria were in the sequence of g-C_(3)N_(4)<RuO_(2)/g-C_(3)N_(4)<Pt/g-C_(3)N_(4)<Pt/RuO_(2)/g-C_(3)N_(4).This magnificent photocatalytic ability of Pt/RuO_(2)/g-C_(3)N_(4)can be interpreted by the transfer of holes from g-C_(3)N_(4)to RuO_(2)to facilitate the in situ generation of HClO from Cl^(−)in wastewater,while Pt extracts photogenerated electrons for H_(2)formation to enhance the reaction.The removal of NH_(4)^(+)-N and disinfection effect were more pronounced in simulated seawater than in purewater.The removal efficiency ofNH_(4)^(+)-N increases with an increase in pH of wastewater,while the bactericidal effect was more significant under a lower pH in a pH range of 6–9.In actual seawater aquaculture wastewater,Pt/RuO_(2)/g-C_(3)N_(4)still exhibits effective removal efficiency of NH_(4)^(+)-N and bactericidal performance under sunlight.This study provides an alternative avenue for removement of NH_(4)^(+)-N and bacteria from saline waters under sunlight.展开更多
As modern communication and detection technologies advance at a swift pace,multifunctional electromagnetic interference(EMI)shielding materials with active/positive infrared stealth,hydrophobicity,and electric-thermal...As modern communication and detection technologies advance at a swift pace,multifunctional electromagnetic interference(EMI)shielding materials with active/positive infrared stealth,hydrophobicity,and electric-thermal conversion ability have received extensive attention.Meeting the aforesaid requirements simultaneously remains a huge challenge.In this research,the melamine foam(MF)/polypyrrole(PPy)nanowire arrays(MF@PPy)were fabricated via one-step electrochemical polymerization.The hierarchical MF@PPy foam was composed of three-dimensional PPy micro-skeleton and ordered PPy nanowire arrays.Due to the upwardly grown PPy nanowire arrays,the MF@PPy foam possessed good hydrophobicity ability with a water contact angle of 142.00°and outstanding stability under various harsh environments.Meanwhile,the MF@PPy foam showed excellent thermal insulation property on account of the low thermal conductivity and elongated ligament characteristic of PPy nanowire arrays.Furthermore,taking advantage of the high conductivity(128.2 S m^(-1)),the MF@PPy foam exhibited rapid Joule heating under 3 V,resulting in dynamic infrared stealth and thermal camouflage effects.More importantly,the MF@PPy foam exhibited remarkable EMI shielding effectiveness values of 55.77 dB and 19,928.57 dB cm^(2)g^(-1).Strong EMI shielding was put down to the hierarchically porous PPy structure,which offered outstanding impedance matching,conduction loss,and multiple attenuations.This innovative approach provides significant insights to the development of advanced multifunctional EMI shielding foams by constructing PPy nanowire arrays,showing great applications in both military and civilian fields.展开更多
This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,an...This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra⁃red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon⁃strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate⁃ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor⁃mance was integrated,achieving a temperature measurement accuracy of 0.3℃.展开更多
Using natural minerals to eliminate harmful Cr(Ⅵ)under sustainable sunshine has significant potential.Herein,Palygorskite nanorods were utilized as carriers for the in-situ synthesis of CaIn_(2)S_(4) photocatalysts t...Using natural minerals to eliminate harmful Cr(Ⅵ)under sustainable sunshine has significant potential.Herein,Palygorskite nanorods were utilized as carriers for the in-situ synthesis of CaIn_(2)S_(4) photocatalysts through a simple one-pot thermal process,enabling the efficient reduction of Cr(Ⅵ).With a Palygorskite to CaIn_(2)S_(4) mass ratio of 5%,the conversion rate of Cr(Ⅵ)reached 98%after 60min of visible-light exposure,with a remarkable reaction rate of 0.0633 min^(-1).The effective integration of CaIn_(2)S_(4) with Palygorskite led to a more uniform dispersion of CaIn_(2)S_(4),exposing more reactive sites.Moreover,the establishment of a heterojunction between CaIn_(2)S_(4) and Palygorskite facilitated the transport of photogenerated electrons from CaIn_(2)S_(4),enhancing the efficiency of charge separation.These factors contribute to the improved photocatalytic performance.Additionally,the developed composite photocatalysts demonstrated excellent stability under light exposure and could be reused efficiently.Trapping tests on active substances revealed that e-played key roles in the Cr(Ⅵ)reduction.This research suggests the potential of using natural minerals to fabricate composite photocatalysts capable of effectively removing pollutants from the environment using solar energy.展开更多
Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small targe...Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small target detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting method(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective background suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.展开更多
A visible-light-enabled method for the synthesis ofα-azidoketones has been developed via oxo-azidation of alkenyl silanes with trimethylsilylazide and molecular oxygen under mild conditions.The reaction could be carr...A visible-light-enabled method for the synthesis ofα-azidoketones has been developed via oxo-azidation of alkenyl silanes with trimethylsilylazide and molecular oxygen under mild conditions.The reaction could be carried out in gram scale.Various radical sources,including trifluoromethyl radical,thiocyanate radical,bromide radical,chlorine radical could partici-pate effectively instead of azide radical in the reaction.展开更多
In sub nanometer carbon nanotubes,water exhibits unique dynamic characteristics,and in the high-frequency region of the infrared spectrum,where the stretching vibrations of the internal oxygen-hydrogen(O-H)bonds are c...In sub nanometer carbon nanotubes,water exhibits unique dynamic characteristics,and in the high-frequency region of the infrared spectrum,where the stretching vibrations of the internal oxygen-hydrogen(O-H)bonds are closely related to the hydrogen bonds(H-bonds)network between water molecules.Therefore,it is crucial to analyze the relationship between these two aspects.In this paper,the infrared spectrum and motion characteristics of the stretching vibrations of the O-H bonds in one-dimensional confined water(1DCW)and bulk water(BW)in(6,6)single-walled carbon nanotubes(SWNT)are studied by molecular dynamics simulations.The results show that the stretching vibrations of the two O-H bonds in 1DCW exhibit different frequencies in the infrared spectrum,while the O-H bonds in BW display two identical main frequency peaks.Further analysis using the spring oscillator model reveals that the difference in the stretching amplitude of the O-H bonds is the main factor causing the change in vibration frequency,where an increase in stretching amplitude leads to a decrease in spring stiffness and,consequently,a lower vibration frequency.A more in-depth study found that the interaction of H-bonds between water molecules is the fundamental cause of the increased stretching amplitude and decreased vibration frequency of the O-H bonds.Finally,by analyzing the motion trajectory of the H atoms,the dynamic differences between 1DCW and BW are clearly revealed.These findings provide a new perspective for understanding the behavior of water molecules at the nanoscale and are of significant importance in advancing the development of infrared spectroscopy detection technology.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
Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time perfor...Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.展开更多
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
Metalens technology has been applied extensively in miniaturized and integrated infrared imaging systems.However,due to the high phase dispersion of unit structures,metalens often exhibits chromatic aberration,making ...Metalens technology has been applied extensively in miniaturized and integrated infrared imaging systems.However,due to the high phase dispersion of unit structures,metalens often exhibits chromatic aberration,making broadband achromatic infrared imaging challenging to achieve.In this paper,six different unit structures based on chalcogenide glass are constructed,and their phase-dispersion parameters are analyzed to establish a database.On this basis,using chromatic aberration compensation and parameterized adjoint topology optimization,a broadband achromatic metalens with a numerical aperture of 0.5 is designed by arranging these six unit structures in the far-infrared band.Simulation results show that the metalens achieves near diffraction-limited focusing within the operating wavelength range of 9−11μm,demonstrating the good performance of achromatic aberration with flat focusing efficiency of 54%−58%across all wavelengths.展开更多
基金Supported by the Henan Province Key Research and Development Project(231111211300)the Central Government of Henan Province Guides Local Science and Technology Development Funds(Z20231811005)+2 种基金Henan Province Key Research and Development Project(231111110100)Henan Provincial Outstanding Foreign Scientist Studio(GZS2024006)Henan Provincial Joint Fund for Scientific and Technological Research and Development Plan(Application and Overcoming Technical Barriers)(242103810028)。
文摘The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.
基金partially supported by China Postdoctoral Science Foundation(2023M730741)the National Natural Science Foundation of China(U22B2052,52102432,52202452,62372080,62302078)
文摘The goal of infrared and visible image fusion(IVIF)is to integrate the unique advantages of both modalities to achieve a more comprehensive understanding of a scene.However,existing methods struggle to effectively handle modal disparities,resulting in visual degradation of the details and prominent targets of the fused images.To address these challenges,we introduce Prompt Fusion,a prompt-based approach that harmoniously combines multi-modality images under the guidance of semantic prompts.Firstly,to better characterize the features of different modalities,a contourlet autoencoder is designed to separate and extract the high-/low-frequency components of different modalities,thereby improving the extraction of fine details and textures.We also introduce a prompt learning mechanism using positive and negative prompts,leveraging Vision-Language Models to improve the fusion model's understanding and identification of targets in multi-modality images,leading to improved performance in downstream tasks.Furthermore,we employ bi-level asymptotic convergence optimization.This approach simplifies the intricate non-singleton non-convex bi-level problem into a series of convergent and differentiable single optimization problems that can be effectively resolved through gradient descent.Our approach advances the state-of-the-art,delivering superior fusion quality and boosting the performance of related downstream tasks.Project page:https://github.com/hey-it-s-me/PromptFusion.
基金supported by Universiti Teknologi MARA through UiTM MyRA Research Grant,600-RMC 5/3/GPM(053/2022).
文摘Infrared and visible image fusion technology integrates the thermal radiation information of infrared images with the texture details of visible images to generate more informative fused images.However,existing methods often fail to distinguish salient objects from background regions,leading to detail suppression in salient regions due to global fusion strategies.This study presents a mask-guided latent low-rank representation fusion method to address this issue.First,the GrabCut algorithm is employed to extract a saliency mask,distinguishing salient regions from background regions.Then,latent low-rank representation(LatLRR)is applied to extract deep image features,enhancing key information extraction.In the fusion stage,a weighted fusion strategy strengthens infrared thermal information and visible texture details in salient regions,while an average fusion strategy improves background smoothness and stability.Experimental results on the TNO dataset demonstrate that the proposed method achieves superior performance in SPI,MI,Qabf,PSNR,and EN metrics,effectively preserving salient target details while maintaining balanced background information.Compared to state-of-the-art fusion methods,our approach achieves more stable and visually consistent fusion results.The fusion code is available on GitHub at:https://github.com/joyzhen1/Image(accessed on 15 January 2025).
基金supported by the National Natural Science Foundation of China[Grant Nos.42205086 and 42122038]。
文摘Mixed-phase clouds(MPCs)involve complex microphysical and dynamical processes of cloud formation and dissipation,which are crucial for numerical weather prediction and cloud-climate feedback.However,satellite remote sensing of MPC properties is still challenging,and there is seldom MPC result inferred from passive spectral observations.This study examines the spectral characteristics of MPCs in the shortwave-infrared(SWIR)channels over the wavelength of 0.4–2.5μm,and evaluates the potential of current operational satellite spectroradiometer channels for MPC retrievals.With optical properties of MPCs based on the assumption of uniform mixing of both ice and liquid water particles,the effects of MPC ice optical thickness fraction(IOTF)and effective radius on associated optical properties are analyzed.As expected,results indicate that the MPC optical properties show features for ice and liquid water clouds,and their spectral variations show noticeable differences from those for homogeneous cases.A radiative transfer method is employed to examine the sensitivity of SWIR channels to given MPC cloud water path(CWP)and IOTF.MPCs have unique signal characteristics in the SWIR spectrum.The 0.87-μm channel is most sensitive to CWP.Meanwhile,the 1.61-and 2.13-μm channels are more sensitive to water-dominated MPCs(IOTF approaching 0),and the 2.25-μm channel is sensitive to both water-dominated and ice-dominated MPCs(IOTF approaching 1).Such spectral differences are potentially possible to be used to infer MPC properties based on radiometer observations,which will be investigated in future studies.
基金This researchwas Sponsored by Xinjiang Uygur Autonomous Region Tianshan Talent Programme Project(2023TCLJ02)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01C349).
文摘Infrared and visible light image fusion technology integrates feature information from two different modalities into a fused image to obtain more comprehensive information.However,in low-light scenarios,the illumination degradation of visible light images makes it difficult for existing fusion methods to extract texture detail information from the scene.At this time,relying solely on the target saliency information provided by infrared images is far from sufficient.To address this challenge,this paper proposes a lightweight infrared and visible light image fusion method based on low-light enhancement,named LLE-Fuse.The method is based on the improvement of the MobileOne Block,using the Edge-MobileOne Block embedded with the Sobel operator to perform feature extraction and downsampling on the source images.The intermediate features at different scales obtained are then fused by a cross-modal attention fusion module.In addition,the Contrast Limited Adaptive Histogram Equalization(CLAHE)algorithm is used for image enhancement of both infrared and visible light images,guiding the network model to learn low-light enhancement capabilities through enhancement loss.Upon completion of network training,the Edge-MobileOne Block is optimized into a direct connection structure similar to MobileNetV1 through structural reparameterization,effectively reducing computational resource consumption.Finally,after extensive experimental comparisons,our method achieved improvements of 4.6%,40.5%,156.9%,9.2%,and 98.6%in the evaluation metrics Standard Deviation(SD),Visual Information Fidelity(VIF),Entropy(EN),and Spatial Frequency(SF),respectively,compared to the best results of the compared algorithms,while only being 1.5 ms/it slower in computation speed than the fastest method.
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.
基金National Natural Science Foundation of China (60802084)
文摘This article proposes a novel method to fuse infrared and visible light images based on region segmentation. Region segmen-tation is used to determine important regions and background information in the input image. The non-subsampled contourlet transform (NSCT) provides a flexible multiresolution,local and directional image expansion,and also a sparse representation for two-dimensional (2-D) piecewise smooth signal building images,and then different fusion rules are applied to fuse the NSCT coefficients fo...
基金supported by the National Natural Science Foundation of China(Nos.52071053,U1704253,and 52103334).
文摘Traditional stealth materials do not fulfill the requirements of high absorption for radar waves and low emissivity for infrared waves.Furthermore,they can be detected by various technologies,considerably threatening weapon safety.Therefore,a stealth material compatible with radar and infrared was designed based on the photonic bandgap characteristics of photonic crystals.The radar stealth lay-er(bottom layer)is a composite of carbonyl iron/silicon dioxide/epoxy resin,and the infrared stealth layer(top layer)is a 1D photonic crystal with alternately and periodically stacked germanium and silicon nitride.Through composition optimization and structural adjust-ment,the effective absorption bandwidth of the compatible stealth material with a reflection loss of less than-10 dB has reached 4.95 GHz.The average infrared emissivity of the proposed design is 0.1063,indicating good stealth performance.The theoretical analysis proves that photonic crystals with this structural design can produce infrared waves within the photonic bandgap,achieving high radar wave transmittance and low infrared emissivity.Infrared stealth is achieved without affecting the absorption performance of the radar stealth layer,and the conflict between radar and infrared stealth performance is resolved.This work aims to promote the application of photonic crystals in compatible stealth materials and the development of stealth technology and to provide a design and theoretical found-ation for related experiments and research.
基金supported by the Science and Technology Planning Project of Fujian Province(No.2023Y4015)the Marine and Fishery Development Special Fund of Xiamen(No.23YYST064QCB36)the Natural Science Foundation of Fujian Province(No.2021J011210).
文摘The removal of ammonia nitrogen(NH_(4)^(+)-N)and bacteria from aquaculture wastewater holds paramount ecological and production significance.In this study,Pt/RuO_(2)/g-C_(3)N_(4)photocatalysts were prepared by depositing Pt and RuO_(2)particles onto g-C_(3)N_(4).The physicochemical properties of photocatalysts were explored by X-ray photoelectron spectroscopy(XPS),scanning electron microscopy(SEM),X-ray diffraction(XRD),and UV–vis diffuse reflectance spectrometer(UV–vis DRS).The photocatalysts were then applied to the removal of both NH_(4)^(+)-N and bacteria from simulated mariculture wastewater.The results clarified that the removals of both NH_(4)^(+)-N and bacteria were in the sequence of g-C_(3)N_(4)<RuO_(2)/g-C_(3)N_(4)<Pt/g-C_(3)N_(4)<Pt/RuO_(2)/g-C_(3)N_(4).This magnificent photocatalytic ability of Pt/RuO_(2)/g-C_(3)N_(4)can be interpreted by the transfer of holes from g-C_(3)N_(4)to RuO_(2)to facilitate the in situ generation of HClO from Cl^(−)in wastewater,while Pt extracts photogenerated electrons for H_(2)formation to enhance the reaction.The removal of NH_(4)^(+)-N and disinfection effect were more pronounced in simulated seawater than in purewater.The removal efficiency ofNH_(4)^(+)-N increases with an increase in pH of wastewater,while the bactericidal effect was more significant under a lower pH in a pH range of 6–9.In actual seawater aquaculture wastewater,Pt/RuO_(2)/g-C_(3)N_(4)still exhibits effective removal efficiency of NH_(4)^(+)-N and bactericidal performance under sunlight.This study provides an alternative avenue for removement of NH_(4)^(+)-N and bacteria from saline waters under sunlight.
基金supported by the Key Research and Development Program of Sichuan Province(Grant No.2023ZHCG0050)the Fundamental Research Funds for the Central Universities of China(Grant No.2682024QZ006 and 2682024ZTPY042)the Analytic and Testing Center of Southwest Jiaotong University.
文摘As modern communication and detection technologies advance at a swift pace,multifunctional electromagnetic interference(EMI)shielding materials with active/positive infrared stealth,hydrophobicity,and electric-thermal conversion ability have received extensive attention.Meeting the aforesaid requirements simultaneously remains a huge challenge.In this research,the melamine foam(MF)/polypyrrole(PPy)nanowire arrays(MF@PPy)were fabricated via one-step electrochemical polymerization.The hierarchical MF@PPy foam was composed of three-dimensional PPy micro-skeleton and ordered PPy nanowire arrays.Due to the upwardly grown PPy nanowire arrays,the MF@PPy foam possessed good hydrophobicity ability with a water contact angle of 142.00°and outstanding stability under various harsh environments.Meanwhile,the MF@PPy foam showed excellent thermal insulation property on account of the low thermal conductivity and elongated ligament characteristic of PPy nanowire arrays.Furthermore,taking advantage of the high conductivity(128.2 S m^(-1)),the MF@PPy foam exhibited rapid Joule heating under 3 V,resulting in dynamic infrared stealth and thermal camouflage effects.More importantly,the MF@PPy foam exhibited remarkable EMI shielding effectiveness values of 55.77 dB and 19,928.57 dB cm^(2)g^(-1).Strong EMI shielding was put down to the hierarchically porous PPy structure,which offered outstanding impedance matching,conduction loss,and multiple attenuations.This innovative approach provides significant insights to the development of advanced multifunctional EMI shielding foams by constructing PPy nanowire arrays,showing great applications in both military and civilian fields.
基金Supported by the Fundamental Research Funds for the Central Universities(2024300443)the Natural Science Foundation of Jiangsu Province(BK20241224).
文摘This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra⁃red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon⁃strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate⁃ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor⁃mance was integrated,achieving a temperature measurement accuracy of 0.3℃.
基金supported by the National Natural Science Foundation of China(Nos.22206065 and 22109059)the Jinling Institute of Technology's Doctor Start-up Fund(No.jitb-202024)the Natural Science Foundation of Jiangsu Province(No.BK20221167).
文摘Using natural minerals to eliminate harmful Cr(Ⅵ)under sustainable sunshine has significant potential.Herein,Palygorskite nanorods were utilized as carriers for the in-situ synthesis of CaIn_(2)S_(4) photocatalysts through a simple one-pot thermal process,enabling the efficient reduction of Cr(Ⅵ).With a Palygorskite to CaIn_(2)S_(4) mass ratio of 5%,the conversion rate of Cr(Ⅵ)reached 98%after 60min of visible-light exposure,with a remarkable reaction rate of 0.0633 min^(-1).The effective integration of CaIn_(2)S_(4) with Palygorskite led to a more uniform dispersion of CaIn_(2)S_(4),exposing more reactive sites.Moreover,the establishment of a heterojunction between CaIn_(2)S_(4) and Palygorskite facilitated the transport of photogenerated electrons from CaIn_(2)S_(4),enhancing the efficiency of charge separation.These factors contribute to the improved photocatalytic performance.Additionally,the developed composite photocatalysts demonstrated excellent stability under light exposure and could be reused efficiently.Trapping tests on active substances revealed that e-played key roles in the Cr(Ⅵ)reduction.This research suggests the potential of using natural minerals to fabricate composite photocatalysts capable of effectively removing pollutants from the environment using solar energy.
基金Supported by the Key Laboratory Fund for Equipment Pre-Research(6142207210202)。
文摘Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small target detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting method(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective background suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.
文摘A visible-light-enabled method for the synthesis ofα-azidoketones has been developed via oxo-azidation of alkenyl silanes with trimethylsilylazide and molecular oxygen under mild conditions.The reaction could be carried out in gram scale.Various radical sources,including trifluoromethyl radical,thiocyanate radical,bromide radical,chlorine radical could partici-pate effectively instead of azide radical in the reaction.
基金Supported by the Natural Science Foundation of China(51705326,52075339)。
文摘In sub nanometer carbon nanotubes,water exhibits unique dynamic characteristics,and in the high-frequency region of the infrared spectrum,where the stretching vibrations of the internal oxygen-hydrogen(O-H)bonds are closely related to the hydrogen bonds(H-bonds)network between water molecules.Therefore,it is crucial to analyze the relationship between these two aspects.In this paper,the infrared spectrum and motion characteristics of the stretching vibrations of the O-H bonds in one-dimensional confined water(1DCW)and bulk water(BW)in(6,6)single-walled carbon nanotubes(SWNT)are studied by molecular dynamics simulations.The results show that the stretching vibrations of the two O-H bonds in 1DCW exhibit different frequencies in the infrared spectrum,while the O-H bonds in BW display two identical main frequency peaks.Further analysis using the spring oscillator model reveals that the difference in the stretching amplitude of the O-H bonds is the main factor causing the change in vibration frequency,where an increase in stretching amplitude leads to a decrease in spring stiffness and,consequently,a lower vibration frequency.A more in-depth study found that the interaction of H-bonds between water molecules is the fundamental cause of the increased stretching amplitude and decreased vibration frequency of the O-H bonds.Finally,by analyzing the motion trajectory of the H atoms,the dynamic differences between 1DCW and BW are clearly revealed.These findings provide a new perspective for understanding the behavior of water molecules at the nanoscale and are of significant importance in advancing the development of infrared spectroscopy detection technology.
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.
基金supported by the National Key Research and Development Project of China(No.2023YFB3709605)the National Natural Science Foundation of China(No.62073193)the National College Student Innovation Training Program(No.202310422122)。
文摘Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.
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.
文摘Metalens technology has been applied extensively in miniaturized and integrated infrared imaging systems.However,due to the high phase dispersion of unit structures,metalens often exhibits chromatic aberration,making broadband achromatic infrared imaging challenging to achieve.In this paper,six different unit structures based on chalcogenide glass are constructed,and their phase-dispersion parameters are analyzed to establish a database.On this basis,using chromatic aberration compensation and parameterized adjoint topology optimization,a broadband achromatic metalens with a numerical aperture of 0.5 is designed by arranging these six unit structures in the far-infrared band.Simulation results show that the metalens achieves near diffraction-limited focusing within the operating wavelength range of 9−11μm,demonstrating the good performance of achromatic aberration with flat focusing efficiency of 54%−58%across all wavelengths.
