In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,eff...In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,efficiently combining the advantages of both images while overcoming their shortcomings is necessary.To handle this challenge,we developed an end-to-end IRI andVI fusionmethod based on frequency decomposition and enhancement.By applying concepts from frequency domain analysis,we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information from the VIs,respectively,significantly boosting the image fusion quality and effectiveness.In addition,the backbone network combined Restormer Blocks and Dense Blocks;Restormer blocks utilize global attention to extract shallow features.Meanwhile,Dense Blocks ensure the integration between shallow and deep features,thereby avoiding the loss of shallow attributes.Extensive experiments on TNO and MSRS datasets demonstrated that the suggested method achieved state-of-the-art(SOTA)performance in various metrics:Entropy(EN),Mutual Information(MI),Standard Deviation(SD),The Structural Similarity Index Measure(SSIM),Fusion quality(Qabf),MI of the pixel(FMI_(pixel)),and modified Visual Information Fidelity(VIF_(m)).展开更多
Cross-band camouflage technology is a critical necessity,enabling personnel and equipment to evade detection across evolving surveillance systems,thereby enhancing survivability and mission success.Herein,this work de...Cross-band camouflage technology is a critical necessity,enabling personnel and equipment to evade detection across evolving surveillance systems,thereby enhancing survivability and mission success.Herein,this work develops a layer-structured composite system based on carbon nanotube(CNT)film comprising ionic liquid(IL)interlayer for infrared(IR)modulation and surface-engineered Cu_(2)O nanoparticles for visible camouflage.The CNT/IL/CNT architecture enables reversible IR emissivity switching(Δε≈0.55)through electrically driven ion intercalation/deintercalation within 2 s,while spray-coated Cu_(2)O nanoparticles(100~400 nm diameter)on the top CNT film layer generate rich structure colors with 90%IR transmittance.This spectral-decoupling design overcomes the traditional trade-off between color visibility and IR transmittance observed in pigment-based systems.Remarkably,due to physical interface coupling,the Cu_(2)O-coated layer-structured system maintains exceptional electrical conductivity,enabling simultaneous electromagnetic interference shielding and electrothermal energy conversion.The integrated system demonstrates long-term operational stability.By unifying visible-IR camouflage,electromagnetic protection,and energy management in a lightweight platform,this work provides an important paradigm for cross-band camouflage technologies.展开更多
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 purpose of infrared and visible image fusion is to create a single image containing the texture details and significant object information of the source images,particularly in challenging environments.However,exis...The purpose of infrared and visible image fusion is to create a single image containing the texture details and significant object information of the source images,particularly in challenging environments.However,existing image fusion algorithms are generally suitable for normal scenes.In the hazy scene,a lot of texture information in the visible image is hidden,the results of existing methods are filled with infrared information,resulting in the lack of texture details and poor visual effect.To address the aforementioned difficulties,we propose a haze-free infrared and visible fusion method,termed HaIVFusion,which can eliminate the influence of haze and obtain richer texture information in the fused image.Specifically,we first design a scene information restoration network(SIRNet)to mine the masked texture information in visible images.Then,a denoising fusion network(DFNet)is designed to integrate the features extracted from infrared and visible images and remove the influence of residual noise as much as possible.In addition,we use color consistency loss to reduce the color distortion resulting from haze.Furthermore,we publish a dataset of hazy scenes for infrared and visible image fusion to promote research in extreme scenes.Extensive experiments show that HaIVFusion produces fused images with increased texture details and higher contrast in hazy scenes,and achieves better quantitative results,when compared to state-ofthe-art image fusion methods,even combined with state-of-the-art dehazing methods.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
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
Objective:To investigate the effects of infrared lamp irradiation therapy on the risk of arteriovenous fistula thrombosis in patients undergoing heparin-free dialysis and those receiving appropriate reductions in hepa...Objective:To investigate the effects of infrared lamp irradiation therapy on the risk of arteriovenous fistula thrombosis in patients undergoing heparin-free dialysis and those receiving appropriate reductions in heparin anticoagulation dosage during dialysis.Methods:This study was conducted from January 1,2021,to December 31,2021,involving 19 patients who regularly underwent heparin-free dialysis for more than three months at our hospital,totaling 70 patient encounters.Each patient underwent heparin-free dialysis for more than two cycles during the experimental period.The study employed a self-control design.Prior to the experiment,an experienced medical team established an emergency management group and formulated relevant emergency measures,ensuring the long-term stability of patients’vital signs before enrollment.Patients requiring heparin-free dialysis as per medical advice underwent the procedure according to the treatment manual without additional interventions.During the second heparin-free dialysis session within the experimental period,patients received 40 minutes of infrared lamp irradiation as an adjunctive therapy during the dialysis process.The study observed coagulation in the dialyzer,blood biochemical indicators,the occurrence of adverse reactions,and patient satisfaction during treatment.Results:The use of heparin-free dialysis combined with infrared irradiation therapy resulted in better coagulation outcomes compared to heparin-free dialysis alone(p<0.05).There was no statistically significant difference in blood biochemical indicators between patients receiving heparin-free dialysis combined with infrared irradiation therapy and those receiving heparin-free dialysis alone(p>0.05).There was no statistically significant difference in the number of patients experiencing adverse clinical symptoms such as angina,dizziness,and lower limb cramps,leading to treatment interruption,between those receiving heparin-free dialysis combined with infrared therapy and those receiving heparin-free dialysis alone(p>0.05).Patient satisfaction was higher among those receiving heparin-free dialysis combined with infrared therapy compared to those receiving heparin-free dialysis alone(p<0.05).Conclusion:The use of infrared lamp irradiation therapy as an adjunct to heparin-free dialysis can reduce the risk of coagulation to a certain extent without affecting the stability of core blood biochemical indicators in patients.It also reduces the incidence of clinical adverse reactions caused by coagulation,demonstrating good safety and improving patient satisfaction.展开更多
The airborne diffusion of saliva droplets during respiratory activities is one of the major factors in the spread of infections.During the COVID-19 pandemic,the use of protective face masks was essential to reduce the...The airborne diffusion of saliva droplets during respiratory activities is one of the major factors in the spread of infections.During the COVID-19 pandemic,the use of protective face masks was essential to reduce the risk of infection and spread of SARS-CoV-2.The face mask is able to significantly reduce the saliva droplet emission in front of the person.However,the use of masks also produces a particle leakage towards the back of the person,which could increase the infection risk of people behind the subject.Most of the experimental investigations applied invasive and/or complex experimental techniques to evaluate the face masks leakage.The primary objective of this study is to develop a novel,non-invasive methodology for assessing rearward droplet emission associated with the use of protective face masks.Specifically,a thermographic analysis of the thermal footprint released during ordinary and extraordinary respiratory activities is presented,evaluating the maximum temperature,the detection time,and the spread area of the thermal footprint.Both surgical and FFP2 face masks were tested.Two different subjects were involved in the experimentation to evaluate the influence of face conformation.The findings indicate that the area influenced by droplet dispersion is larger when wearing a surgical mask compared to an FFP2 mask,with the highest recorded temperatures observed for the surgical mask.The thermal footprint was found to be strongly dependent on individual facial morphology and mask fit.Notably,the FFP2 mask also altered the position of the thermal footprint,which was primarily confined to the region near the neck.展开更多
Compact size,high brightness,and wide field of view(FOV)are key requirements for long-wave infrared imagers used in military surveillance or night navigation.However,to meet the imaging requirements of high resolution...Compact size,high brightness,and wide field of view(FOV)are key requirements for long-wave infrared imagers used in military surveillance or night navigation.However,to meet the imaging requirements of high resolution and wide FOV,infrared optical systems often adopt complex optical lens groups,which will increase the size and weight of the optical system.In this paper,a strategy based on wavefront coding(WFC)is proposed to design a compact wide-FOV infrared imager.A cubic phase mask is inserted into the pupil plane of the infrared imager to correct the aberration.The simulated results show that,the WFC infrared imager has good imaging quality in a wide FOV of±16°.In addition,the WFC infrared imager achieves compactness with its 40 mm×40 mm×40 mm size.A fast focal ratio of 1 combined with an entrance pupil diameter of 25 mm ensures brightness.This work is of significance for designing a compact wide-FOV infrared imager.展开更多
Improving the optoelectronic behavior and stress-deformation stability of conjugated materials is crucial for the realization of their potential applications in flexible optoelectronics.To tune the emission behavior a...Improving the optoelectronic behavior and stress-deformation stability of conjugated materials is crucial for the realization of their potential applications in flexible optoelectronics.To tune the emission behavior and mechanical property of molecular crystals simultaneously via supramolecular salt strategy is rarely reported,which is very important to improve their photophysical behavior and softness for the fabrication of flexible light-emitting device.Herein,supramolecular salt approach has been successfully applied to synthesize two elastic organic fluorescent crystals(CMOH-Py-Cl and CMOH-Py-Br)derived from non-emissive and brittle pyridine-substituted coumarin derivative(CMOH-Py).Their elastic properties can be attributed to the prevalent presence of numerous weak interactions introduced by halogen atoms,which are beneficial to the absorption and release of mechanical energy.Furthermore,density functional theory(DFT)calculations demonstrated a narrowing of the HOMO-LUMO energy gaps from CMOH-Py to CMOH-Py-Cl/CMOH-Py-Br via supramolecular salt approach.Finally,the application of flexible crystal materials in the field of optical waveguides has been investigated.The transformation of crystals in terms of photophysical and mechanical properties,achieved by the supramolecular salt approach,offers novel insights into the design and construction of flexible crystalline materials,providing a new path for the development of next-generation smart materials.展开更多
Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article ha...Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article has been corrected.展开更多
Sensor noise is a critical factor that degrades the performance of image processing systems.In traditional computing systems,noise correction is implemented in the digital domain,resulting in redundant latency and pow...Sensor noise is a critical factor that degrades the performance of image processing systems.In traditional computing systems,noise correction is implemented in the digital domain,resulting in redundant latency and power consumption overhead in the analog-to-digital conversion.In this work,we propose an analog-domain image correction architecture based on a proposed small-scale UNet,which implements a compact noise correction network within a one-transistor-one-memristor(1T1R)array.The statistical non-idealities of the fabricated 1T1R array(e.g.,device variability)are rigorously incorporated into the network's training and inference simulations.This correction network architecture leverages memristors for conducting multiply-accumulate operations aimed at rectifying non-uniform noise,defective pixels(stuck-at-bright/dark),and exposure mismatch.Compared to systems without correction,the proposed architecture achieves up to 50.13%improvement in recognition accuracy while demonstrating robust tolerance to memristor device-level errors.The proposed system achieves a 2.13-fold latency reduction and three orders of magnitude higher energy efficiency compared to conventional architecture.This work establishes a new paradigm for advancing the development of low-power,low-latency,and high-precision image processing systems.展开更多
The matching performance among the visible and near infrared coating.the low infrared emitting coating and the microwave absorbing coating was investigated.Experimental results show that the resulting malerial is char...The matching performance among the visible and near infrared coating.the low infrared emitting coating and the microwave absorbing coating was investigated.Experimental results show that the resulting malerial is characteristic of wideband effect ranging from the visible,near infrared and 3-5μm,8-14μm infrared protion of the spectrum,as well as the radar region from 8 to 18GHz when these three materials form αlayerstructure material system.The microwave absorbing ability of material is hardly changed.The resonance peak moves towards lower frequency as the thickness of the visible,near infrared coating and the low infrared emitting coating increases.This problem can be resolved by controlling the thickness of the matrial.On the other hand, the infrared emissivity εof the material system increases as the thickness of the visible,near infrared coating increases.This can be resolved by increasing infrared transparency of the visible and near infrared topcoating or controlling its thickness.The experimental resulting material system has spectral reflection characteristics in visible and near infrared regions that are similar to those of the natural background.展开更多
Image fusion is a key technology in the field of digital image processing.In the present study,an effect-based pseudo color fusion model of infrared and visible images based on the rattlesnake vision imaging system(th...Image fusion is a key technology in the field of digital image processing.In the present study,an effect-based pseudo color fusion model of infrared and visible images based on the rattlesnake vision imaging system(the rattlesnake bimodal cell fusion mechanism and the visual receptive field model)is proposed.The innovation point of the proposed model lies in the following three features:first,the introduction of a simple mathematical model of the visual receptive field reduce computational complexity;second,the enhanced image is obtained by extracting the common information and unique information of source images,which improves fusion image quality;and third,the Waxman typical fusion structure is improved for the pseudo color image fusion model.The performance of the image fusion model is verified through comparative experiments.In the subjective visual evaluation,we find that the color of the fusion image obtained through the proposed model is natural and can highlight the target and scene details.In the objective quantitative evaluation,we observe that the best values on the four indicators,namely standard deviation,average gradient,entropy,and spatial frequency,accounts for 90%,100%,90%,and 100%,respectively,indicating that the fusion image exhibits superior contrast,image clarity,information content,and overall activity.Experimental results reveal that the performance of the proposed model is superior to that of other models and thus verified the validity and reliability of the model.展开更多
Traditional techniques based on image fusion are arduous in integrating complementary or heterogeneous infrared(IR)/visible(VS)images.Dissimilarities in various kind of features in these images are vital to preserve i...Traditional techniques based on image fusion are arduous in integrating complementary or heterogeneous infrared(IR)/visible(VS)images.Dissimilarities in various kind of features in these images are vital to preserve in the single fused image.Hence,simultaneous preservation of both the aspects at the same time is a challenging task.However,most of the existing methods utilize the manual extraction of features;and manual complicated designing of fusion rules resulted in a blurry artifact in the fused image.Therefore,this study has proposed a hybrid algorithm for the integration of multi-features among two heterogeneous images.Firstly,fuzzification of two IR/VS images has been done by feeding it to the fuzzy sets to remove the uncertainty present in the background and object of interest of the image.Secondly,images have been learned by two parallel branches of the siamese convolutional neural network(CNN)to extract prominent features from the images as well as high-frequency information to produce focus maps containing source image information.Finally,the obtained focused maps which contained the detailed integrated information are directly mapped with the source image via pixelwise strategy to result in fused image.Different parameters have been used to evaluate the performance of the proposed image fusion by achieving 1.008 for mutual information(MI),0.841 for entropy(EG),0.655 for edge information(EI),0.652 for human perception(HP),and 0.980 for image structural similarity(ISS).Experimental results have shown that the proposed technique has attained the best qualitative and quantitative results using 78 publically available images in comparison to the existing discrete cosine transform(DCT),anisotropic diffusion&karhunen-loeve(ADKL),guided filter(GF),random walk(RW),principal component analysis(PCA),and convolutional neural network(CNN)methods.展开更多
Multi-source information can be obtained through the fusion of infrared images and visible light images,which have the characteristics of complementary information.However,the existing acquisition methods of fusion im...Multi-source information can be obtained through the fusion of infrared images and visible light images,which have the characteristics of complementary information.However,the existing acquisition methods of fusion images have disadvantages such as blurred edges,low contrast,and loss of details.Based on convolution sparse representation and improved pulse-coupled neural network this paper proposes an image fusion algorithm that decompose the source images into high-frequency and low-frequency subbands by non-subsampled Shearlet Transform(NSST).Furthermore,the low-frequency subbands were fused by convolutional sparse representation(CSR),and the high-frequency subbands were fused by an improved pulse coupled neural network(IPCNN)algorithm,which can effectively solve the problem of difficulty in setting parameters of the traditional PCNN algorithm,improving the performance of sparse representation with details injection.The result reveals that the proposed method in this paper has more advantages than the existing mainstream fusion algorithms in terms of visual effects and objective indicators.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
基金funded by Anhui Province University Key Science and Technology Project(2024AH053415)Anhui Province University Major Science and Technology Project(2024AH040229)+3 种基金Talent Research Initiation Fund Project of Tongling University(2024tlxyrc019)Tongling University School-Level Scientific Research Project(2024tlxyptZD07)TheUniversity Synergy Innovation Programof Anhui Province(GXXT-2023-050)Tongling City Science and Technology Major Special Project(Unveiling and Commanding Model)(200401JB004).
文摘In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,efficiently combining the advantages of both images while overcoming their shortcomings is necessary.To handle this challenge,we developed an end-to-end IRI andVI fusionmethod based on frequency decomposition and enhancement.By applying concepts from frequency domain analysis,we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information from the VIs,respectively,significantly boosting the image fusion quality and effectiveness.In addition,the backbone network combined Restormer Blocks and Dense Blocks;Restormer blocks utilize global attention to extract shallow features.Meanwhile,Dense Blocks ensure the integration between shallow and deep features,thereby avoiding the loss of shallow attributes.Extensive experiments on TNO and MSRS datasets demonstrated that the suggested method achieved state-of-the-art(SOTA)performance in various metrics:Entropy(EN),Mutual Information(MI),Standard Deviation(SD),The Structural Similarity Index Measure(SSIM),Fusion quality(Qabf),MI of the pixel(FMI_(pixel)),and modified Visual Information Fidelity(VIF_(m)).
基金Financial support from the National Nature Science Foundation of China(No.:52373244)the Foundation of National Science and Technology Key Laboratory(No.:KZ571801)。
文摘Cross-band camouflage technology is a critical necessity,enabling personnel and equipment to evade detection across evolving surveillance systems,thereby enhancing survivability and mission success.Herein,this work develops a layer-structured composite system based on carbon nanotube(CNT)film comprising ionic liquid(IL)interlayer for infrared(IR)modulation and surface-engineered Cu_(2)O nanoparticles for visible camouflage.The CNT/IL/CNT architecture enables reversible IR emissivity switching(Δε≈0.55)through electrically driven ion intercalation/deintercalation within 2 s,while spray-coated Cu_(2)O nanoparticles(100~400 nm diameter)on the top CNT film layer generate rich structure colors with 90%IR transmittance.This spectral-decoupling design overcomes the traditional trade-off between color visibility and IR transmittance observed in pigment-based systems.Remarkably,due to physical interface coupling,the Cu_(2)O-coated layer-structured system maintains exceptional electrical conductivity,enabling simultaneous electromagnetic interference shielding and electrothermal energy conversion.The integrated system demonstrates long-term operational stability.By unifying visible-IR camouflage,electromagnetic protection,and energy management in a lightweight platform,this work provides an important paradigm for cross-band camouflage technologies.
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supported by the Natural Science Foundation of Shandong Province,China(ZR2022MF237)the National Natural Science Foundation of China Youth Fund(62406155)the Major Innovation Project(2023JBZ02)of Qilu University of Technology(Shandong Academy of Sciences).
文摘The purpose of infrared and visible image fusion is to create a single image containing the texture details and significant object information of the source images,particularly in challenging environments.However,existing image fusion algorithms are generally suitable for normal scenes.In the hazy scene,a lot of texture information in the visible image is hidden,the results of existing methods are filled with infrared information,resulting in the lack of texture details and poor visual effect.To address the aforementioned difficulties,we propose a haze-free infrared and visible fusion method,termed HaIVFusion,which can eliminate the influence of haze and obtain richer texture information in the fused image.Specifically,we first design a scene information restoration network(SIRNet)to mine the masked texture information in visible images.Then,a denoising fusion network(DFNet)is designed to integrate the features extracted from infrared and visible images and remove the influence of residual noise as much as possible.In addition,we use color consistency loss to reduce the color distortion resulting from haze.Furthermore,we publish a dataset of hazy scenes for infrared and visible image fusion to promote research in extreme scenes.Extensive experiments show that HaIVFusion produces fused images with increased texture details and higher contrast in hazy scenes,and achieves better quantitative results,when compared to state-ofthe-art image fusion methods,even combined with state-of-the-art dehazing methods.
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.
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2023 Hospital-Level Scientific Research and New Technology Project Initiation of Wuzhong People’s Hospital(Project No.:2023yjxjs05)。
文摘Objective:To investigate the effects of infrared lamp irradiation therapy on the risk of arteriovenous fistula thrombosis in patients undergoing heparin-free dialysis and those receiving appropriate reductions in heparin anticoagulation dosage during dialysis.Methods:This study was conducted from January 1,2021,to December 31,2021,involving 19 patients who regularly underwent heparin-free dialysis for more than three months at our hospital,totaling 70 patient encounters.Each patient underwent heparin-free dialysis for more than two cycles during the experimental period.The study employed a self-control design.Prior to the experiment,an experienced medical team established an emergency management group and formulated relevant emergency measures,ensuring the long-term stability of patients’vital signs before enrollment.Patients requiring heparin-free dialysis as per medical advice underwent the procedure according to the treatment manual without additional interventions.During the second heparin-free dialysis session within the experimental period,patients received 40 minutes of infrared lamp irradiation as an adjunctive therapy during the dialysis process.The study observed coagulation in the dialyzer,blood biochemical indicators,the occurrence of adverse reactions,and patient satisfaction during treatment.Results:The use of heparin-free dialysis combined with infrared irradiation therapy resulted in better coagulation outcomes compared to heparin-free dialysis alone(p<0.05).There was no statistically significant difference in blood biochemical indicators between patients receiving heparin-free dialysis combined with infrared irradiation therapy and those receiving heparin-free dialysis alone(p>0.05).There was no statistically significant difference in the number of patients experiencing adverse clinical symptoms such as angina,dizziness,and lower limb cramps,leading to treatment interruption,between those receiving heparin-free dialysis combined with infrared therapy and those receiving heparin-free dialysis alone(p>0.05).Patient satisfaction was higher among those receiving heparin-free dialysis combined with infrared therapy compared to those receiving heparin-free dialysis alone(p<0.05).Conclusion:The use of infrared lamp irradiation therapy as an adjunct to heparin-free dialysis can reduce the risk of coagulation to a certain extent without affecting the stability of core blood biochemical indicators in patients.It also reduces the incidence of clinical adverse reactions caused by coagulation,demonstrating good safety and improving patient satisfaction.
文摘The airborne diffusion of saliva droplets during respiratory activities is one of the major factors in the spread of infections.During the COVID-19 pandemic,the use of protective face masks was essential to reduce the risk of infection and spread of SARS-CoV-2.The face mask is able to significantly reduce the saliva droplet emission in front of the person.However,the use of masks also produces a particle leakage towards the back of the person,which could increase the infection risk of people behind the subject.Most of the experimental investigations applied invasive and/or complex experimental techniques to evaluate the face masks leakage.The primary objective of this study is to develop a novel,non-invasive methodology for assessing rearward droplet emission associated with the use of protective face masks.Specifically,a thermographic analysis of the thermal footprint released during ordinary and extraordinary respiratory activities is presented,evaluating the maximum temperature,the detection time,and the spread area of the thermal footprint.Both surgical and FFP2 face masks were tested.Two different subjects were involved in the experimentation to evaluate the influence of face conformation.The findings indicate that the area influenced by droplet dispersion is larger when wearing a surgical mask compared to an FFP2 mask,with the highest recorded temperatures observed for the surgical mask.The thermal footprint was found to be strongly dependent on individual facial morphology and mask fit.Notably,the FFP2 mask also altered the position of the thermal footprint,which was primarily confined to the region near the neck.
文摘Compact size,high brightness,and wide field of view(FOV)are key requirements for long-wave infrared imagers used in military surveillance or night navigation.However,to meet the imaging requirements of high resolution and wide FOV,infrared optical systems often adopt complex optical lens groups,which will increase the size and weight of the optical system.In this paper,a strategy based on wavefront coding(WFC)is proposed to design a compact wide-FOV infrared imager.A cubic phase mask is inserted into the pupil plane of the infrared imager to correct the aberration.The simulated results show that,the WFC infrared imager has good imaging quality in a wide FOV of±16°.In addition,the WFC infrared imager achieves compactness with its 40 mm×40 mm×40 mm size.A fast focal ratio of 1 combined with an entrance pupil diameter of 25 mm ensures brightness.This work is of significance for designing a compact wide-FOV infrared imager.
基金supported by the National Natural Science Foundation of China(Nos.22205105,61874053,22075136)National Key Basic Research Program of China(No.2020YFA0709900)Jiangsu Provincial Postgraduate Scientific Research Innovation Program(No.KYCX24_1649).
文摘Improving the optoelectronic behavior and stress-deformation stability of conjugated materials is crucial for the realization of their potential applications in flexible optoelectronics.To tune the emission behavior and mechanical property of molecular crystals simultaneously via supramolecular salt strategy is rarely reported,which is very important to improve their photophysical behavior and softness for the fabrication of flexible light-emitting device.Herein,supramolecular salt approach has been successfully applied to synthesize two elastic organic fluorescent crystals(CMOH-Py-Cl and CMOH-Py-Br)derived from non-emissive and brittle pyridine-substituted coumarin derivative(CMOH-Py).Their elastic properties can be attributed to the prevalent presence of numerous weak interactions introduced by halogen atoms,which are beneficial to the absorption and release of mechanical energy.Furthermore,density functional theory(DFT)calculations demonstrated a narrowing of the HOMO-LUMO energy gaps from CMOH-Py to CMOH-Py-Cl/CMOH-Py-Br via supramolecular salt approach.Finally,the application of flexible crystal materials in the field of optical waveguides has been investigated.The transformation of crystals in terms of photophysical and mechanical properties,achieved by the supramolecular salt approach,offers novel insights into the design and construction of flexible crystalline materials,providing a new path for the development of next-generation smart materials.
文摘Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article has been corrected.
基金Project supported by the National Key Research and Development Program of China(Grant No.2024YFA1208800)the National Natural Science Foundation of China(Grant Nos.62404253,62304254,U23A20322)。
文摘Sensor noise is a critical factor that degrades the performance of image processing systems.In traditional computing systems,noise correction is implemented in the digital domain,resulting in redundant latency and power consumption overhead in the analog-to-digital conversion.In this work,we propose an analog-domain image correction architecture based on a proposed small-scale UNet,which implements a compact noise correction network within a one-transistor-one-memristor(1T1R)array.The statistical non-idealities of the fabricated 1T1R array(e.g.,device variability)are rigorously incorporated into the network's training and inference simulations.This correction network architecture leverages memristors for conducting multiply-accumulate operations aimed at rectifying non-uniform noise,defective pixels(stuck-at-bright/dark),and exposure mismatch.Compared to systems without correction,the proposed architecture achieves up to 50.13%improvement in recognition accuracy while demonstrating robust tolerance to memristor device-level errors.The proposed system achieves a 2.13-fold latency reduction and three orders of magnitude higher energy efficiency compared to conventional architecture.This work establishes a new paradigm for advancing the development of low-power,low-latency,and high-precision image processing systems.
文摘The matching performance among the visible and near infrared coating.the low infrared emitting coating and the microwave absorbing coating was investigated.Experimental results show that the resulting malerial is characteristic of wideband effect ranging from the visible,near infrared and 3-5μm,8-14μm infrared protion of the spectrum,as well as the radar region from 8 to 18GHz when these three materials form αlayerstructure material system.The microwave absorbing ability of material is hardly changed.The resonance peak moves towards lower frequency as the thickness of the visible,near infrared coating and the low infrared emitting coating increases.This problem can be resolved by controlling the thickness of the matrial.On the other hand, the infrared emissivity εof the material system increases as the thickness of the visible,near infrared coating increases.This can be resolved by increasing infrared transparency of the visible and near infrared topcoating or controlling its thickness.The experimental resulting material system has spectral reflection characteristics in visible and near infrared regions that are similar to those of the natural background.
基金supported by the National Natural Science Foundation of China(NSFC)under grant numbers 61201368.
文摘Image fusion is a key technology in the field of digital image processing.In the present study,an effect-based pseudo color fusion model of infrared and visible images based on the rattlesnake vision imaging system(the rattlesnake bimodal cell fusion mechanism and the visual receptive field model)is proposed.The innovation point of the proposed model lies in the following three features:first,the introduction of a simple mathematical model of the visual receptive field reduce computational complexity;second,the enhanced image is obtained by extracting the common information and unique information of source images,which improves fusion image quality;and third,the Waxman typical fusion structure is improved for the pseudo color image fusion model.The performance of the image fusion model is verified through comparative experiments.In the subjective visual evaluation,we find that the color of the fusion image obtained through the proposed model is natural and can highlight the target and scene details.In the objective quantitative evaluation,we observe that the best values on the four indicators,namely standard deviation,average gradient,entropy,and spatial frequency,accounts for 90%,100%,90%,and 100%,respectively,indicating that the fusion image exhibits superior contrast,image clarity,information content,and overall activity.Experimental results reveal that the performance of the proposed model is superior to that of other models and thus verified the validity and reliability of the model.
文摘Traditional techniques based on image fusion are arduous in integrating complementary or heterogeneous infrared(IR)/visible(VS)images.Dissimilarities in various kind of features in these images are vital to preserve in the single fused image.Hence,simultaneous preservation of both the aspects at the same time is a challenging task.However,most of the existing methods utilize the manual extraction of features;and manual complicated designing of fusion rules resulted in a blurry artifact in the fused image.Therefore,this study has proposed a hybrid algorithm for the integration of multi-features among two heterogeneous images.Firstly,fuzzification of two IR/VS images has been done by feeding it to the fuzzy sets to remove the uncertainty present in the background and object of interest of the image.Secondly,images have been learned by two parallel branches of the siamese convolutional neural network(CNN)to extract prominent features from the images as well as high-frequency information to produce focus maps containing source image information.Finally,the obtained focused maps which contained the detailed integrated information are directly mapped with the source image via pixelwise strategy to result in fused image.Different parameters have been used to evaluate the performance of the proposed image fusion by achieving 1.008 for mutual information(MI),0.841 for entropy(EG),0.655 for edge information(EI),0.652 for human perception(HP),and 0.980 for image structural similarity(ISS).Experimental results have shown that the proposed technique has attained the best qualitative and quantitative results using 78 publically available images in comparison to the existing discrete cosine transform(DCT),anisotropic diffusion&karhunen-loeve(ADKL),guided filter(GF),random walk(RW),principal component analysis(PCA),and convolutional neural network(CNN)methods.
基金supported in part by the National Natural Science Foundation of China under Grant 41505017.
文摘Multi-source information can be obtained through the fusion of infrared images and visible light images,which have the characteristics of complementary information.However,the existing acquisition methods of fusion images have disadvantages such as blurred edges,low contrast,and loss of details.Based on convolution sparse representation and improved pulse-coupled neural network this paper proposes an image fusion algorithm that decompose the source images into high-frequency and low-frequency subbands by non-subsampled Shearlet Transform(NSST).Furthermore,the low-frequency subbands were fused by convolutional sparse representation(CSR),and the high-frequency subbands were fused by an improved pulse coupled neural network(IPCNN)algorithm,which can effectively solve the problem of difficulty in setting parameters of the traditional PCNN algorithm,improving the performance of sparse representation with details injection.The result reveals that the proposed method in this paper has more advantages than the existing mainstream fusion algorithms in terms of visual effects and objective indicators.
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.
