Accurate and efficient identification and segmentation of gases play an important role in industrial processes and public safety. Although Optical Gas Imaging (OGI) has proven effective in acquiring images and videos of gas leaks, accurately determining the leakage points and their diffusion areas in real-world conditions remains a significant challenge. To address this, we propose a novel gas segmentation annotation methodology. This approach applies differencing between gas leakage scenes and corresponding static background to delineate precise leakage regions, which are subsequently annotated manually. The resulting dataset, consisting of 926 static background-gas image pairs extracted from 38 comprehensive video sequences, provides a robust foundation for advancing gas segmentation research. Based on this dataset, we present a novel semantic segmentation model specifically designed for the unique characteristics of gas leakage scenarios. Our model integrates a gas contrast attention mechanism to capitalize on static background information, resulting in improved segmentation precision. Comparative evaluations demonstrate that the proposed model achieves state-of-the-art performance on our dataset, outperforming widely adopted semantic segmentation models. All code and the dataset will be made publicly available at https://github.com/ProAlize/CGNet.

Underwater optical imaging plays a crucial role in maritime safety, enabling reliable navigation, efficient search and rescue operations, precise target recognition, and robust military reconnaissance. However, conventional underwater imaging methods often suffer from severe backscattering noise, limited detection range, and reduced image clarity—challenges that are exacerbated in turbid waters. To address these issues, Underwater Laser Range-Gated Imaging has emerged as a promising solution. By selectively capturing photons within a controlled temporal gate, this technique effectively suppresses backscattering noise-enhancing image clarity, contrast, and detection range. Nevertheless, residual noise within the imaging slice can still degrade image quality, particularly in challenging underwater conditions. In this study, we propose an enhanced U-Net neural network designed to mitigate noise interference in underwater laser range-gated images, improving target recognition performance. Built upon the U-Net architecture with added residual connections, our network combines a VGG16-based perceptual loss with Mean Squared Error (MSE) as the loss function, effectively capturing high-level semantic features while preserving critical target details during reconstruction. Trained on a semi-synthetic grayscale dataset containing synthetically degraded images paired with their reference counterparts, the proposed approach demonstrates improved performance compared to several existing underwater image restoration methods in our experimental evaluations. Through comprehensive qualitative and quantitative evaluations, underwater target detection experiments, and real-world oceanic validations, our method demonstrates significant potential for advancing maritime safety and related applications.

Laser range-gated underwater imaging technology, by removing most of the backscattering noise, can effectively increase image contrast and extend the detection range. The optical signal captured by a range-gated imaging system primarily comprises reflected light from the object and backscattered light from the surrounding water. Consequently, surfaces with low reflectivity or highly turbid water environments substantially constrain the applicability of the range-gated imaging system. To enhance the detection capability of underwater laser range-gated imaging, this paper proposes the incorporation of underwater polarized light imaging technology as an enhancement method. Based on polarization differences, backscattered light and reflected light from an object can be distinguished. Experimental results indicate that, compared to images obtained using a conventional range-gated laser imaging system, those captured with a polarization-enhanced system exhibit an increase of up to 47% for the corresponding Enhancement Measure Evaluation (EME) index. The proposed approach, which integrates polarization imaging with range-gated laser imaging, has the potential to broaden the applicability of underwater laser imaging scenarios, such as deep-sea exploration and military applications.

Infrared imaging technology is a useful tool for detecting gas leaks due to its significant advantages in detection spacial range, efficiency, and visualization. However, the original infrared images of gas leak traces often suffer from low contrast due to a small thermal radiation intensity difference between the gas plume and the scene. So it is difficult to directly separate them in the grayscale histogram distribution. Traditional enhancement methods lack targeted optimizations for traces of leaking gas. Therefore, enhancing the trace of gas leaks is crucial to the performance of gas leak detection systems based on infrared imaging. In this paper, we propose an image enhancement method based on guided filtering, the visibility restoration algorithm. The proposed method comprises three stages: image decomposition, base and detail layer enhancement, and image fusion output. We selected three infrared images of gas leakage taken in different scenes for experiments. There are obvious differences in the original images taken from the three scenes. We compare the image enhancement result of Histogram Equalization(HE), Contrast Limited Adaptive Histogram Equalization (CLAHE) and our proposed method. The image enhanced by our proposed has the highest values of quantitative indicators: average gradient(AG) and Enhancement Measure Evaluation(EME); which are three times higher than the original image. By visual observation, the gas leak plume in the images enhanced by our proposed method are obvious significantly.

Infrared imaging systems have been widely applied in gas leak detection. However, The existing gas detection methods have many limitations and are difficult to apply in real-world scenarios. At the same time, there are very few methods that combine gas detection and semantic segmentation with deep learning. In this study, a novel approach for gas detection using image semantic segmentation in deep learning is proposed. This method presents a new multi-scale semantic segmentation model named PUNet, based on PSPNet and U-Net, for automatic segmentation of infrared gas leakage images. Meanwhile, to solve the problems of single scene and fixed leakage location in the gas leakage image dataset, we added more self-collected infrared gas leakage images to the existing dataset. The experimental findings demonstrate that PUNet has higher accuracy than traditional foreground segmentation algorithm and outperforms the conventional U-Net model in segmenting gas leakage images, and exhibits enhanced efficacy in handling multi-scale gas leakage scenarios.

由于水体对电磁波的吸收与散射,水下光学成像存在"看不远"和"看不清"的问题,而水下激光距离选通成像技术可以提高水下光学成像距离和图像对比度.该文介绍了以水下激光距离选通成像技术为基础的水下远距离目标智能识别系统研究.实验结果显示,成像距离超过 7 倍衰减长度.该研究结合深度学习算法,在功率受限的硬件条件下,实现了目标的准实时检测,检测速度达 0.8 f/s.水下激光距离选通成像技术与深度学习算法的结合,有望实现水下光学成像"看得远"和"看得清"的同时,实现"看得快"和"看得准".

Aiming at the bad performances of existing traditional local stereo matching methods in ill-posed regions, an improved AD-Census algorithm based on two-phase adaptive optimization and gradient fusion is proposed. During the cross arm construction phase, an adaptive nonlinear constraint of intensity difference between pixels is adopted to get the optimal arm length. In the cost computation phase, the absolute difference(AD) cost and Census transform(CT) cost of each pixel are weighted summed firstly. Then the result is fused with the gradient cost by adaptive weight, which is determined by the exponential function with the shortest arm length as the independent variable. Finally, the disparity map is obtained by cost aggregation, disparity selection and disparity refinement. The experimental results indicate that the average disparity error of all regions on Middlebury 2014 datasets is reduced by 31% compared with the original AD-Census algorithm, and the average disparity error of non-occlusion regions is reduced by 40%. The proposed algorithm performs better in textureless regions and disparity discontinuity regions, and it shows enough robustness for radiometric changes and noise.

Iris extraction is a crucial step in iris recognition technology. However, it is easily interfered with by eyelashes. In the process of iris recognition, the detection of eyelashes is very significant when taking iris images. But the precision of the existing iris detection algorithm is not high. This paper proposes an eyelash segmentation method based on the adaptive threshold. Firstly, a specific area in the picture is selected as the region of interest according to the position of the eyelashes. Then the gray range of the area is defined according to the iris gray information. Finally, under the above two constraints, the optimal threshold of gray-scale image segmentation is calculated using the algorithm of maximizing variance between classes. The method improves the subjective accuracy of eyelash segmentation in the iris image and lays the foundation for the next step of iris recognition.

We numerically investigate the thermal effects in a cornea illuminated by terahertz radiation. By modifying the bioheat and Arrhenius equations, we studied the heat-transfer and temperature distributions in the corneal tissue, and evaluated the potential thermal damage. The influence of the beam radius and power density are discussed. We also estimated the effective cornea-collagen shrinkage region, and evaluated the degree of thermal damage in the cornea. We expect this work to open up a novel effective and safe thermal-treatment approach based on THz radiation for cornea reshaping in the field of ophthalmology.

The objective of this study is to test the feasibility of RuMoC films for its application in seedless Cu diffusion barriers of damascene structure. The compatibility with integral circuit (IC) fabrication and thermal stability of RuMoC barriers were investigated. The RuMoC barriers are amorphous at temperatures up to 500 degrees C, showing great thermal stability. This is because the Ru-C bonds are well preserved at those temperatures, as revealed by XPS results, which hinder the Ru from crystallizing. A Cu plug of good quality was successfully electroplated on RuMoC barriers and filled the trench without seed layer, and the barrier effectively block the diffusion of Cu atom at temperatures up to 500 degrees C.

As one of the most reliable biometric identification techniques, iris recognition has focused on the differences in iris textures without considering the similarities. In this work, we investigate the correlation between the left and right irises of an individual using a VGG16 convolutional neural network. Experimental results with two independent iris datasets show that a remarkably high classification accuracy of larger than 94% can be achieved when identifying if two irises (left and right) are from the same or different individuals. This exciting finding suggests that the similarities between genetically identical irises that are indistinguishable using traditional Daugman’s approaches can be detected by deep learning. We expect this work will shed light on further studies on the correlation between irises and/or other biometric identifiers of genetically identical or related individuals, which would find potential applications in criminal investigations.

We show that ultrasensitive THz sensors can be achieved based on corrugated hyperbolic metamaterials. For the proposed sensor the sensitivity of the proposed sensor reaches 1 THz/RIU (9.3 × 10 3 nmlRIU), which is orders of magnitude larger than those based on metasurfaces.

Ultrathin graded ZrNx self-assembled diffusion barriers with controllable stoichiometry was prepared in Cu/p-SiOC:H interfaces by plasma immersion ion implantation (PIII) with dynamic regulation of implantation fluence. The fundamental relationship between the implantation fluence of N+ and the stoichiometry and thereby the electrical properties of the ZrNx barrier was established. The optimized fluence of a graded ZrN thin film with gradually decreased Zr valence was obtained with the best electrical performance as well. The Cu/p-SiOC: H integration is thermally stable up to 500 degrees C due to the synergistic effect of Cu3Ge and ZrNx layers. Accordingly, the PIII process was verified in a 100-nm-thick Cu dual-damascene interconnect, in which the ZrNx diffusion barrier of 1 nm thick was successfully self-assembled on the sidewall without barrier layer on the via bottom. In this case, the via resistance was reduced by approximately 50% in comparison with Ta/TaN barrier. Considering the results in this study, ultrathin ZrNx conformal diffusion barrier can be adopted in the sub-14 nm technology node. (C) 2017 Elsevier B.V. All rights reserved.

随着我国海洋战略的提出,对于海洋观测技术和装备的需求日趋迫切。针对现有水下成像系统无法实现精确三维测量这一难题,该文提出了一种基于双目立体视觉原理的水下三维测量系统研究方法,并对其可行性进行了验证。针对水下成像过程存在的水体界面折射问题,该文提出了相应的相机成像模型及系统参数标定方法,建立了防水深度达30 m的双目水下测量及照明装置,并在水池、近海条件下进行了实地测试。实验结果显示,在水体条件较好的情况下,系统观测距离可达8 m以上,有效测量距离为0.5~4.5 m,在0.5 m和4.5 m距离处的测量误差分别为2 mm和20 mm。实验验证了水下双目成像模型、立体标定、测量模型等方法的有效性和精确性,可为水下检修作业等海洋工程行业提供一种有效的三维测量技术手段。

Cu dual-damascene interconnects with an amorphous Ru–Mo–C (labeled as RuMoC) seedless barrier layer were successfully fabricated and its feasibility for advanced Cu dual-damascene interconnects were investigated. The results show that the RuMoC II films obtained with sputtering rates (Ru:MoC) of 100:50 demonstrated the best performance, exhibiting an amorphous structure, low residual oxygen content, low resistivity at temperatures up to 500 °C. A Cu plug of good quality was successfully electroplated on the RuMoC II barrier layer with 4-nm-thick without seed layer in a damascene structure. The ultra-thin RuMoC II barrier effectively blocked the diffusion of Cu and O atom after being annealed up to 500 °C. The damascene structure showed much lower leakage current and via resistance compared to the damascene structures with traditional Ta barrier, suggesting that RuMoC II film has sufficient barrier properties. Moreover, the via resistance of the damascene structures with RuMoC II barrier were quite low and met the requirement of different technology nodes for the future semiconductor industry, indicating great prospects for advanced seedless Cu metallization applications.

The detection of corona discharge is an effective way for early fault diagnosis of power equipment. UV-Visible dual-band imaging can detect and locate corona discharge spot at all-weather condition. In this study, we introduce an image registration protocol for this dual-band imaging system. The protocol consists of UV image denoising and affine transformation model establishment. We report the algorithm details of UV image preprocessing, affine transformation model establishment and relevant experiments for verification of their feasibility. The denoising algorithm was based on a correlation operation between raw UV images, a continuous mask and the transformation model was established by using corner feature and a statistical method. Finally, an image fusion test was carried out to verify the accuracy of affine transformation model. It has proved the average position displacement error between corona discharge and equipment fault at different distances in a 2.5m-20 m range are 1.34 mm and 1.92 nun in the horizontal and vertical directions, respectively, which are precise enough for most industrial applications. The resultant protocol is not only expected to improve the efficiency and accuracy of such imaging system for locating corona discharge spot, but also supposed to provide a more generalized reference for the calibration of various dual-band imaging systems in practice. (C) 2018 Elsevier Ltd. All rights reserved.

Waveguides made of hyperbolic metamaterials have unique properties such as extremely high field enhancement. Here we show that hyperbolic slot waveguides, i.e., nanoscale plasmonic slot waveguides cladded by hyperbolic metamaterials can have greatly enhanced Kerr nonlinear effects at even shorter device lengths and lower pump power compared with the conventional metallic slot waveguides. This result points to novel nanoscale waveguide designs for achieving low-driving-power and compact nonlinear nanophotonic devices that are used in diverse applications at both classical and quantum levels.

Cu has been adopted to replace Al for conduction lines and contact structures in very large-scale integrated circuits due to its low resistivity. However, Cu could rapidly react with the SiO2-based dielectric under 300 degrees C and form deep level impurities which are strong sink for carriers, leading to the dielectric degradation of the devices. Therefore, it is important to insert a stable barrier between the Cu wiring and SiO2-based dielectric for suppressing Cu diffusion and improving the adhesive strength. The prediction of international technology roadmap for semiconductors that the thickness of diffusion barrier would be further reduced to 3 nm for 22 nm technology node indicates the widely being used Ta/TaN barrier would be incompetent in the future, since Ta/TaN barrier at the limited thickness exhibits a high resistivity and a columnar grain structure which provides lots of vertical grain boundaries for Cu diffusion. Therefore a directly platable amorphous single barrier with low resistivity is highly desired. In this work, MoC are chosen as impurity to expect for amorphous Ru-based films. The RuMoC films with different components were deposited by RE magnetron co-sputtering with different deposition power ratios of MoC versus Ru targets. The sheet resistances, microstructures and components of the RuMoC films in Ru-MoC/Si and Cu/RuMoC/p-SiOC: H/Si structures were studied. The sheet resistances, residual oxygen contents and microstructures of the RuMoC films have close correlation with the doping contents of Mo and C elements which can be easily controlled by tuning the deposition power on MoC target. When the deposition power ratio of MoC versus Ru targets was 0.5, amorphous RuMoC II film with low sheet resistance and residual oxygen content was obtained. After annealing at 500 degrees C the Mo-C and Ru-C bonds were well-preserved and co-suppressed the recrystallization of the film and the increasing of the oxygen content, contributing to excellent thermal stability and electrical properties of Cu/RuMoC II/p-SiOC: H/Si film.

To improve the phase reconstruction accuracy of two-step phase-shifting interferometry measurement method, a phase blind demodulation algorithm based on zoned background estimation is proposed. In the algorithm, a sequence of zero value points in interferograms are picked out as seeds. A Voronoi figure surrounding these seeds is created, and the Voronoi figure segments each interferogram into several zones. The background of all points in these zones is set as the seed background, and a whole background is obtained when we combine these seed backgrounds. Numerical simulation and experimental analysis are conducted. Numerical simulation results show that the root-mean-square error (RMSE) of demodulation phase of the proposed algorithm is close to that of the method with real background. Experimental results show that the demodulation phase RMSE is reduced by 16％ compared with the traditional low-pass filtering method.

Viewing an airborne scene from a totally submerged camera will suffer severe refractive distortions due to the water surface random fluctuation. One way to reduce this distortion is to use a wave sensor to image a known guide star, through which the water wave surface is measured and reconstructed. In the wave reconstruction, a wave equivalent plane is needed to determine the positions of the wave normal vector samples. The equivalent plane is determined by measuring the under water depth of the wave sensor using a pressure-based gauge. This way can't reveal the overall wave distribution and the reading is usually haphazard. In this paper, a novel wave equivalent plane estimation method based on the incident rays parallelism is presented. Computer simulation results show that the derived plane with the minimum reconstructed sampling position error (PMPE) is the ideal equivalent plane, and the estimated plane based on the incident rays parallelism is in agreement with PMPE. Experiment results are also presented.