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

A novel image fusion network framework with an autonomous encoder and decoder is suggested to increase thevisual impression of fused images by improving the quality of infrared and visible light picture fusion. The networkcomprises an encoder module, fusion layer, decoder module, and edge improvementmodule. The encoder moduleutilizes an enhanced Inception module for shallow feature extraction, then combines Res2Net and Transformerto achieve deep-level co-extraction of local and global features from the original picture. An edge enhancementmodule (EEM) is created to extract significant edge features. A modal maximum difference fusion strategy isintroduced to enhance the adaptive representation of information in various regions of the source image, therebyenhancing the contrast of the fused image. The encoder and the EEM module extract features, which are thencombined in the fusion layer to create a fused picture using the decoder. Three datasets were chosen to test thealgorithmproposed in this paper. The results of the experiments demonstrate that the network effectively preservesbackground and detail information in both infrared and visible images, yielding superior outcomes in subjectiveand objective evaluations.

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

To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is proposed.The region attention module is meant to extract the background feature map based on the distinct properties of the background feature map and the detail feature map.A multi-scale convolution attention module is suggested to enhance the communication of feature information.At the same time,the feature transformation module is introduced to learn more robust feature representations,aiming to preserve the integrity of image information.This study uses three available datasets from TNO,FLIR,and NIR to perform thorough quantitative and qualitative trials with five additional algorithms.The methods are assessed based on four indicators:information entropy(EN),standard deviation(SD),spatial frequency(SF),and average gradient(AG).Object detection experiments were done on the M3FD dataset to further verify the algorithm’s performance in comparison with five other algorithms.The algorithm’s accuracy was evaluated using the mean average precision at a threshold of 0.5(mAP@0.5)index.Comprehensive experimental findings show that CAEFusion performs well in subjective visual and objective evaluation criteria and has promising potential in downstream object detection tasks.

RMPC-Based Visual Servoing for Trajectory Tracking of Quadrotor UAVs With Visibility Constraints

Dear Editor,This letter deals with the tracking problem of quadrotors subject to external disturbances and visibility constraints by designing a robust model predictive control(RMPC) scheme. According to the imagebased visual servoing(IBVS) method, a virtual camera is constructed to express image moments of the tracking target.

Development of D_α band symmetrical visible optical diagnostic for boundary reconstruction on EAST tokamak

To investigate the potential of utilizing visible spectral imaging for controlling the plasma boundary shape during stable operation of plasma in future tokamak, a D_α band symmetric visible light diagnostic system was designed and implemented on the Experimental Advanced Superconducting Tokamak(EAST). This system leverages two symmetric optics for joint plasma imaging. The optical system exhibits a spatial resolution less than 2 mm at the poloidal cross-section, distortion within the field of view below 10%, and relative illumination of 91%.The high-quality images obtained enable clear observation of both the plasma boundary position and the characteristics of components within the vacuum vessel. Following system calibration and coordinate transformation, the image coordinate boundary features are mapped to the tokamak coordinate system. Utilizing this system, the plasma boundary was reconstructed, and the resulting representation showed alignment with the EFIT(Equilibrium Fitting) results. This underscores the system's superior performance in boundary reconstruction applications and provides a diagnostic foundation for boundary shape control based on visible spectral imaging.

High-visibility ghost imaging with phase-controlled discrete classical light sources

We take phase modulation to create discrete phase-controlled sources and realize the super-bunching effect by a phasecorrelated method. From theoretical and numerical simulations, we find the space translation invariance of the bunching effect is a key point for the ghost imaging realization. Experimentally, we create the orderly phase-correlated discrete sources which can realize high-visibility second-order ghost imaging than the result with chaotic sources. Moreover, some factors affecting the visibility of ghost image are discussed in detail.

Deep learning-assisted common temperature measurement based on visible light imaging

Real-time,contact-free temperature monitoring of low to medium range(30℃-150℃)has been extensively used in industry and agriculture,which is usually realized by costly infrared temperature detection methods.This paper proposes an alternative approach of extracting temperature information in real time from the visible light images of the monitoring target using a convolutional neural network(CNN).A mean-square error of<1.119℃was reached in the temperature measurements of low to medium range using the CNN and the visible light images.Imaging angle and imaging distance do not affect the temperature detection using visible optical images by the CNN.Moreover,the CNN has a certain illuminance generalization ability capable of detection temperature information from the images which were collected under different illuminance and were not used for training.Compared to the conventional machine learning algorithms mentioned in the recent literatures,this real-time,contact-free temperature measurement approach that does not require any further image processing operations facilitates temperature monitoring applications in the industrial and civil fields.

An organic visible-photocatalytic-adsorbence mechanism to high-efficient removal of heavy metal antimony ions

Purification of emerging heavy metal antimony contaminated water based on advanced ingenious strategies.An activated modified coconut shell charcoal(CSC)was synthesized and evaluated as a substrate-supported loaded organic photovoltaic material,PM6:PYIT:PM6-b-PYIT,to prepare a surprisingly highly efficient,stable,environmentally friendly,and recyclable organic photocatalyst(CSC–N–P.P.P),which showed excellent effects on the simultaneous removal of Sb(Ⅲ)and Sb(Ⅴ).The removal efficiency of CSC-N-P.P.P on Sb(Ⅲ)and Sb(Ⅴ)reached an amazing 99.9%in quite a short duration of 15 min.At the same time,under ppb level and indoor visible light(~1 W m^(2)),it can be treated to meet the drinking water standards set by the European Union and the U.S.National Environmental Protection Agency in 5 min,and even after 25 cycles of recycling,the efficiency is still maintained at about 80%,in addition to the removal of As(Ⅲ),Cd(Ⅱ),Cr(Ⅵ),and Pb(Ⅱ)can also be realized.The catalyst not only solves the problems of low reuse rate,difficult structure adjustment and high energy consumption of traditional photocatalysts but also has strong applicability and practical significance.The pioneering approach provides a much-needed solution strategy for removing highly toxic heavy metal antimony pollution from the environment.

A CSMA/CA based MAC protocol for hybrid Power-line/Visible-light communication networks:Design and analysis

Hybrid Power-line/Visible-light Communication(HPVC)network has been one of the most promising Cooperative Communication(CC)technologies for constructing Smart Home due to its superior communication reliability and hardware efficiency.Current research on HPVC networks focuses on the performance analysis and optimization of the Physical(PHY)layer,where the Power Line Communication(PLC)component only serves as the backbone to provide power to light Emitting Diode(LED)devices.So designing a Media Access Control(MAC)protocol remains a great challenge because it allows both PLC and Visible Light Communication(VLC)components to operate data transmission,i.e.,to achieve a true HPVC network CC.To solve this problem,we propose a new HPC network MAC protocol(HPVC MAC)based on Carrier Sense Multiple Access/Collision Avoidance(CSMA/CA)by combining IEEE 802.15.7 and IEEE 1901 standards.Firstly,we add an Additional Assistance(AA)layer to provide the channel selection strategies for sensor stations,so that they can complete data transmission on the selected channel via the specified CSMA/CA mechanism,respectively.Based on this,we give a detailed working principle of the HPVC MAC,followed by the construction of a joint analytical model for mathematicalmathematical validation of the HPVC MAC.In the modeling process,the impacts of PHY layer settings(including channel fading types and additive noise feature),CSMA/CA mechanisms of 802.15.7 and 1901,and practical configurations(such as traffic rate,transit buffer size)are comprehensively taken into consideration.Moreover,we prove the proposed analytical model has the solvability.Finally,through extensive simulations,we characterize the HPVC MAC performance under different system parameters and verify the correctness of the corresponding analytical model with an average error rate of 4.62%between the simulation and analytical results.

High-resolution visible imaging with piezoelectric deformable secondary mirror: experimental results at the 1.8-m adaptive telescope

Integrating deformable mirrors within the optical train of an adaptive telescope was one of the major innovations in astronomical observation technology,distinguished by its high optical throughput,reduced optical surfaces,and the incorporation of the deformable mirror.Typically,voice-coil actuators are used,which require additional position sensors,internal control electronics,and cooling systems,leading to a very complex structure.Piezoelectric deformable secondary mirror technologies were proposed to overcome these problems.Recently,a high-order piezoelectric deformable secondary mirror has been developed and installed on the 1.8-m telescope at Lijiang Observatory in China to make it an adaptive telescope.The system consists of a 241-actuator piezoelectric deformable secondary mirror,a 192-sub-aperture Shack-Hartmann wavefront sensor,and a multi-core-based real-time controller.The actuator spacing of the PDSM measures 19.3 mm,equivalent to approximately 12.6 cm when mapped onto the primary mirror,significantly less than the voicecoil-based adaptive telescopes such as LBT,Magellan and VLT.As a result,stellar images with Strehl ratios above 0.49 in the R band have been obtained.To our knowledge,these are the highest R band images captured by an adaptive telescope with deformable secondary mirrors.Here,we report the system description and on-sky performance of this adaptive telescope.

Detection of EEG signals in normal and epileptic seizures with multiscale multifractal analysis approach via weighted horizontal visibility graph

Electroencephalogram(EEG) signals contain important information about the regulation of brain system. Thus, automatic detection of epilepsy by analyzing the characteristics obtained from EEG signals has important research implications in the field of clinical medicine. In this paper, the horizontal visibility graph(HVG) algorithm is used to map multifractal EEG signals into complex networks. Then, we study the structure of the networks and explore the nonlinear dynamics properties of the EEG signals inherited from these networks. In order to better describe complex brain behaviors, we use the angle between two connected nodes as the edge weight of the network and construct the weighted horizontal visibility graph(WHVG). In our studies, fractality and multifractality of WHVG are innovatively used to analyze the structure of related networks. However, these methods only analyze the reconstructed dynamical system in general characterizations,they are not sufficient to describe the complex behavior and cannot provide a comprehensive picture of the system. To this effect, we propose an improved multiscale multifractal analysis(MMA) for network, which extends the description of the network dynamics features by focusing on the relationship between the multifractality and the measured scale-free intervals.Furthermore, neural networks are applied to train the above-mentioned parameters for the classification and identification of three kinds of EEG signals, i.e., health, interictal phase, and ictal phase. By evaluating our experimental results, the classification accuracy is 99.0%, reflecting the effectiveness of the WHVG algorithm in extracting the potential dynamic characteristics of EEG signals.

Comparing simulated and experimental spectral line splitting in visible spectroscopy diagnostics in the HL-2A tokamak

We established the passive-visible spectroscopy diagnostics(P-VSD)and active-VSD(A-VSD)spectral splitting models for the HL-2A tokamak.Spectral splitting due to the influence of electromagnetic fields on the spectra in VSD is studied.Zeeman splitting induced by the magnetic field(B)is used to distinguish reflected light overlap in the divertor for P-VSD.Stark splitting caused by the Lorentz electric field(E_(Lorentz))from the neutral beam injection particle’s interaction with the magnetic field(V_(beam)×B)is used to measure the safety factor q profile for A-VSD.We give a comparison and error analysis by fitting the experimental spectra with the simulation results.The distinguishing of edge(scrape-off layer and divertor)hydrogen/deuterium spectral lines and the q profile derived from the spectra provides a reference for HL-2M VSD.

Channel Capacity and Power Allocation of MIMO Visible Light Communication System

In this paper,the channel capacity of the multiple-input multiple-output(MIMO)visible light communication(VLC)system is investigated under the peak,average optical and electrical power constraints.Finding the channel capacity of MIMO VLC is shown to be a mixed integer programming problem.To address this open problem,we propose an inexact gradient projection method to find the channel capacity-achieving discrete input distribution and the channel capacity of MIMO VLC.Also we derive both upper and lower bounds of the capacity of MIMO VLC with the closed-form expressions.Furthermore,by considering practical discrete constellation inputs,we develop the optimal power allocation scheme to maximize transmission rate of MIMO VLC system.Simulation results show that more discrete points are needed to achieve the channel capacity as SNR increases.Both the upper and lower bounds of channel capacity are tight at low SNR region.In addition,comparing the equal power allocation,the proposed power allocation scheme can significantly increase the rate for the low-order modulation inputs.

Facile one-pot synthesis of a BiOBr/Bi_(2)WO_(6) heterojunction with enhanced visible-light photocatalytic activity for tetracycline degradation

Photocatalytic removal of tetracycline(TC)from the wastewater is of great value in the chemical and environmental engineering field.Here,we introduced a facile one-step method for the synthesis of BiOBr/Bi2WO6 heterojunctions by using cheap CTAB as the Br source.We showed the possibility of our method to fine-tune the content of BiOBr in the produced BiOBr/Bi2WO6 by simply changing the dosage of cetyltrimethylammonium bromide(CTAB),providing a platform for the delicate tuning of the visiblelight absorbance ability of the composites.With a suitable heterojunction structure of BiOBr/Bi2WO6-0.2,it exhibited an ultrarapid photocatalytic activity towards TC(20 mg
L^(-1)),with a competitive removal efficiency of 88.1%within 60 min and an ultrahigh removal rate of 0.0349 min^(-1).It could also be robustly recycled for at least 5 cycles with slight removal efficiency loss.We demonstrated that this exciting photocatalytic performance was due to the highly decreased recombination of photoinduced electrons and holes on our composites by constructing this heterojunction structure,and the resulting
OH and
O^(-)_(2)contributed to the effective degradation of TC to CO_(2).

Characterization of retinal ganglion cell damage at single axon bundle level in mice by visible-light optical coherence tomography fibergraphy

Retinal ganglion cells(RGCs)receive synaptic inputs through their dendritic trees in the inner plexiform layer(IPL)and convey the visual information via their axons which form the optic nerve to the brain(Sanes and Masland,2015).In glaucoma,RGCs and their axons degenerate and die,leading to irreversible vision loss and eventually blindness if left untreated(Quigley,2016).

HY-PC:Enabling Consistent Positioning and Communication Using Visible Light

Visible light(VL)plays an important role in achieving high-precision positioning and low bit error radio(BER)data communication.However,most VL-based systems can not achieve positioning and communication,simultaneously.There are two problems:1)the hybrid systems are difficult to extract distinguishable positioning beacon features without affecting communication performance,2)in the hybrid systems,the lost data bits in the inter-frame gap(IFG)are hard to recover,which affects positioning and communication performance.Therefore,in this article,we propose a novel VL-based hybrid positioning and communication system,named HY-PC system,to solve the above problems.First,we propose the robust T-W mapping for recognizing specific Light Emitting Diodes(LEDs),which can provide stable LED recognition accuracy without adding extra beacon data and does not decrease the communication rate.Furthermore,we also propose the novel linear block coding and bit interleaving mechanism,which can recover the lost data bits in the IFG and improve data communication performance.Finally,we use commercial off-the-shelf devices to implement our HY-PC system,extensive experimental results show that our HY-PC system can achieve consistent high-precision positioning and low-BER data communication,simultaneously.

A betaxanthin-based visible and fluorescent reporter for monitoring plant transformation

Commonly used reporters rely on a single property,such as the fluorescence of GFP and visible color of anthocyanins,therefore these reporters hardly handle the complicated condition in practice.Betaxanthins are a group of plant natural products derived from the amino acid tyrosine.Its visible yellow-orange color and green fluorescence under blue light make it a promising new reporter.Only two enzymatic reactions are required to convert tyrosine into betaxanthins.Here,we synthesized an open reading frame named Bx that contained all the betaxanthins biosynthetic genes and demonstrated its use as a powerful and efficient reporter in tobacco,carrot,and tomato.

Visibility graph approach to extreme event series

An extreme event may lead to serious disaster to a complex system.In an extreme event series there exist generally non-trivial patterns covering different time scales.Investigations on extreme events are currently based upon statistics,where the patterns are merged into averages.In this paper from extreme event series we constructed extreme value series and extreme interval series.And the visibility graph is then adopted to display the patterns formed by the increases/decreases of extreme value or interval faster/slower than the linear ones.For the fractional Brownian motions,the properties for the constructed networks are the persistence,threshold,and event-type-independent,e.g.,the degree distributions decay exponentially with almost identical speeds,the nodes cluster into modular structures with large and similar modularity degrees,and each specific network has a perfect hierarchical structure.For the volatilities of four stock markets(NSDQ,SZI,FTSE100,and HSI),the properties for the former three's networks are threshold-and market-independent.Comparing with the factional Brownian motions,their degree distributions decay exponentially but with slower speeds,their modularity behaviors are significant but with smaller modularity degrees.The fourth market behaves similar qualitatively but different quantitatively with the three markets.Interestingly,all the transition frequency networks share an identical backbone composed of nine edges and the linked graphlets.The universal behaviors give us a framework to describe extreme events from the viewpoint of network.

Development of multi-band and high-speed visible endoscope diagnostic on EAST with catadioptric optics

A new multi-band and high-speed endoscope diagnostic for the observation of visible light has been successfully developed on the Experimental Advanced Superconducting Tokamak.The mirror with an aperture is designed at the head of the optical system.Based on two dichroic mirrors,the system is divided into three imaging mirror groups with different bands,i.e.B(380-500 nm),G(500-580 nm)and R(580-750 nm)bands,and its focal length is 16 mm with a relatively large aperture of D/f=1:4.The spatial resolution is less than 5 mm near the object distance of 1750 mm with the camera NAC ACS-1 M60.This optical system will be used to contrastively study both the spatial distribution and time evolution of different impurities in the same field of view.The experimental results confirm that it can be applied to the recognition of plasma boundary and related physical research.

Visible Light Communication for Vehicular Applications: A Novel Architecture with Proof-of-Concept Prototype

When there is an increasing interest in visible light communication(VLC), outdoor vehicle VLC has emerged as a promising candidate technology for future intelligent transportation systems. However, in VLC based vehicular applications, several challenges impede successful commercial application of VLC based products. This article first provides a thorough overview of the existing challenges. To overcome these challenges, we propose a novel architecture with tracking and environment sensing ability for practical vehicular applications. Moreover, a proof-ofconcept prototype is implemented to validate the feasibility of the proposed system. Experimental and simulation results show that the proposed VLC system can provide reliable communications with a bit-error rate less than 10-4for vehicles under strong interference lights. Finally, based on the evaluations, we propose some key design issues for future studies in this research area.

Adaptive Reversible Visible Watermarking Based on Total Variation for BTC-Compressed Images

Few previous Reversible Visible Watermarking(RVW)schemes have both good transparency and watermark visibility.An adaptive RVW scheme that integrates Total Variation and visual perception in Block Truncation Coding(BTC)compressed domain,called TVB-RVW is proposed in this paper.A new mean image estimation method for BTC-compressed images is first developed with the help of Total Variation.Then,a visual perception factor computation model is devised by fusing texture and luminance characteristics.An adaptive watermark embedding strategy is used to embed the visible watermark with the effect of the visual perception factor in the BTC domain.Moreover,a lossless embedding method of the encrypted visible watermark is exploited to deter illegal watermark removal.The visible watermark can be removed since the visual perception factor and the estimated mean image remain unchanged before and after watermark embedding.Extensive experiments validate the superiority of the proposed algorithm over previous RVW schemes in BTC in terms of the visual quality of watermarked images and watermark visibility,and it can achieve a good balance between transparency and watermark visibility.