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Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

《信息与电子工程前沿（英文）》 2015年第16卷第3期页码 227-237 doi: 10.1631/FITEE.1400217

摘要： We present a novel image fusion scheme based on gradient and scrambled block Hadamard ensemble (SBHE) sampling for compressive sensing imaging. First, source images are compressed by compressive sensing, to facilitate the transmission of the sensor. In the fusion phase, the image gradient is calculated to reflect the abundance of its contour information. By compositing the gradient of each image, gradient-based weights are obtained, with which compressive sensing coefficients are achieved. Finally, inverse transformation is applied to the coefficients derived from fusion, and the fused image is obtained. Information entropy (IE), Xydeas’s and Piella’s metrics are applied as non-reference objective metrics to evaluate the fusion quality in line with different fusion schemes. In addition, different image fusion application scenarios are applied to explore the scenario adaptability of the proposed scheme. Simulation results demonstrate that the gradient-based scheme has the best performance, in terms of both subjective judgment and objective metrics. Furthermore, the gradient-based fusion scheme proposed in this paper can be applied in different fusion scenarios.

关键词： Compressive sensing (CS) Image fusion Gradient-based image fusion CS-based image fusion

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Turbidity-adaptive underwater image enhancement method using image fusion

《机械工程前沿（英文）》 2022年第17卷第3期 doi: 10.1007/s11465-021-0669-8

摘要： Clear, correct imaging is a prerequisite for underwater operations. In real freshwater environment including rivers and lakes, the water bodies are usually turbid and dynamic, which brings extra troubles to quality of imaging due to color deviation and suspended particulate. Most of the existing underwater imaging methods focus on relatively clear underwater environment, it is uncertain that if those methods can work well in turbid and dynamic underwater environments. In this paper, we propose a turbidity-adaptive underwater image enhancement method. To deal with attenuation and scattering of varying degree, the turbidity is detected by the histogram of images. Based on the detection result, different image enhancement strategies are designed to deal with the problem of color deviation and blurring. The proposed method is verified by an underwater image dataset captured in real underwater environment. The result is evaluated by image metrics including structure similarity index measure, underwater color image quality evaluation metric, and speeded-up robust features. Test results exhibit that the method can correct the color deviation and improve the quality of underwater images.

关键词： turbidity underwater image enhancement image fusion underwater robots visibility

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Multi-scale UDCT dictionary learning based highly undersampled MR image reconstruction using patch-based

Min YUAN,Bing-xin YANG,Yi-de MA,Jiu-wen ZHANG,Fu-xiang LU,Tong-feng ZHANG

《信息与电子工程前沿（英文）》 2015年第16卷第12期页码 1069-1087 doi: 10.1631/FITEE.1400423

摘要： Recently, dictionary learning (DL) based methods have been introduced to compressed sensing magnetic resonance imaging (CS-MRI), which outperforms pre-defined analytic sparse priors. However, single-scale trained dictionary directly from image patches is incapable of representing image features from multi-scale, multi-directional perspective, which influences the reconstruction performance. In this paper, incorporating the superior multi-scale properties of uniform discrete curvelet transform (UDCT) with the data matching adaptability of trained dictionaries, we propose a flexible sparsity framework to allow sparser representation and prominent hierarchical essential features capture for magnetic resonance (MR) images. Multi-scale decomposition is implemented by using UDCT due to its prominent properties of lower redundancy ratio, hierarchical data structure, and ease of implementation. Each sub-dictionary of different sub-bands is trained independently to form the multi-scale dictionaries. Corresponding to this brand-new sparsity model, we modify the constraint splitting augmented Lagrangian shrinkage algorithm (C-SALSA) as patch-based C-SALSA (PB C-SALSA) to solve the constraint optimization problem of regularized image reconstruction. Experimental results demonstrate that the trained sub-dictionaries at different scales, enforcing sparsity at multiple scales, can then be efficiently used for MRI reconstruction to obtain satisfactory results with further reduced undersampling rate. Multi-scale UDCT dictionaries potentially outperform both single-scale trained dictionaries and multi-scale analytic transforms. Our proposed sparsity model achieves sparser representation for reconstructed data, which results in fast convergence of reconstruction exploiting PB C-SALSA. Simulation results demonstrate that the proposed method outperforms conventional CS-MRI methods in maintaining intrinsic properties, eliminating aliasing, reducing unexpected artifacts, and removing noise. It can achieve comparable performance of reconstruction with the state-of-the-art methods even under substantially high undersampling factors.

关键词： Compressed sensing (CS) Magnetic resonance imaging (MRI) Uniform discrete curvelet transform (UDCT) Multi-scale dictionary learning (MSDL) Patch-based constraint splitting augmented Lagrangian shrinkage algorithm (PB C-SALSA)

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Advances in polishing of internal structures on parts made by laser-based powder bed fusion

《机械工程前沿（英文）》 2023年第18卷第1期 doi: 10.1007/s11465-022-0724-0

摘要： The internal structures of metallic products are important in realizing functional applications. Considering the manufacturing of inner structures, laser-based powder bed fusion (L-PBF) is an attractive approach because its layering principle enables the fabrication of parts with customized interior structures. However, the inferior surface quality of L-PBF components hinders its productization progress seriously. In this article, process, basic forms, and applications relevant to L-PBF internal structures are reviewed comprehensively. The causes of poor surface quality and differences in the microstructure and property of the surface features of L-PBF inner structures are presented to provide a perspective of their surface characteristics. Various polishing technologies for L-PBF components with inner structures are presented, whereas their strengths and weaknesses are summarized along with a discussion on the challenges and prospects for improving the interior surface quality of L-PBF parts.

关键词： laser-based powder bed fusion polishing internal structures surface quality surface features post process additive manufacturing

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基于分数阶导数和直觉模糊集的多聚焦图像融合 Research Articles

张雪峰,闫慧,何昊

《信息与电子工程前沿（英文）》 2020年第21卷第6期页码 809-962 doi: 10.1631/FITEE.1900737

摘要：多聚焦图像融合在图像融合中日益重要，在图像处理中扮演着关键角色。本文提出一种基于分数阶导数和直觉模糊集的多聚焦图像融合方法。其将原始图像分解为基础层和细节层，建立一个新的分数阶空间频率来反映图像清晰度。采用分数阶空间频率作为细节层融合准则，并引入直觉模糊集对基础层进行融合。实验结果表明，该方法在多聚焦图像融合方面优于已有先进方法。

关键词：像融合；分数阶导数；直觉模糊集；多聚焦图像

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Static analysis of corrugated panels using homogenization models and a cell-based smoothed mindlin plateelement (CS-MIN3)

Nhan NGUYEN-MINH, Nha TRAN-VAN, Thang BUI-XUAN, Trung NGUYEN-THOI

《结构与土木工程前沿（英文）》 2019年第13卷第2期页码 251-272 doi: 10.1007/s11709-017-0456-0

摘要： Homogenization is a promising approach to capture the behavior of complex structures like corrugated panels. It enables us to replace high-cost shell models with stiffness-equivalent orthotropic plate alternatives. Many homogenization models for corrugated panels of different shapes have been proposed. However, there is a lack of investigations for verifying their accuracy and reliability. In addition, in the recent trend of development of smoothed finite element methods, the cell-based smoothed three-node Mindlin plate element (CS-MIN3) based on the first-order shear deformation theory (FSDT) has been proposed and successfully applied to many analyses of plate and shell structures. Thus, this paper further extends the CS-MIN3 by integrating itself with homogenization models to give homogenization methods. In these methods, the equivalent extensional, bending, and transverse shear stiffness components which constitute the equivalent orthotropic plate models are represented in explicit analytical expressions. Using the results of ANSYS and ABAQUS shell simulations as references, some numerical examples are conducted to verify the accuracy and reliability of the homogenization methods for static analyses of trapezoidally and sinusoidally corrugated panels.

关键词： homogenization corrugated panel asymptotic analysis smoothed finite element method (S-FEM) cell-based smoothed three-node Mindlin plate element (CS-MIN3)

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基于全卷积网络的多焦距图像融合算法 Research Articles

郭瑞1,2,申铉京1,2,董小瑜1,2,张小利1,2

《信息与电子工程前沿（英文）》 2020年第21卷第7期页码 963-1118 doi: 10.1631/FITEE.1900336

摘要：提出一种多焦距图像融合方法，在该算法中构造用于焦点检测的全卷积网络（fully convolutional network for focus detection，FD-FCN）。为获得更精确的焦点检测图谱，在该网络中添加跳层，从而在生成图谱过程中同时提供详细和抽象的视觉信息。基于数据集CIFAR-10，为该网络构建一个新的训练数据集。运用FD-FCN的图像融合算法包含3个步骤：使用FD-FCN获得焦点图谱，通过对焦点图谱进行形态学处理生成决策图，使用决策图进行图像融合。开展了多组实验，主客观评估结果均表明该融合方法优于同类先进算法。

关键词：多焦距图像融合；全卷积网络；跳层；性能评估

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Catalytic hydrogenation of insoluble organic matter of CS/Acetone from coal over mesoporous HZSM-5 supported

《化学科学与工程前沿（英文）》 2022年第16卷第10期页码 1505-1513 doi: 10.1007/s11705-022-2164-0

摘要： Four supported catalysts, nickel and ruthenium on a HZSM-5 support, were prepared by equal volume impregnation and in-situ decomposition of carbonyl nickel. The properties of catalysts were investigated by catalytic hydro-conversion of 2,2′-dinaphthyl ether as the model compound and extraction residue of Naomaohu lignite as the sample under an initial H₂ pressure of 5 MPa and temperature at 150 °C. According to the catalytic hydro-conversion results of the model compound, Ni−Ru/HZSM-5 exhibited the best catalytic performance. It not only activated H₂ into H···H, but also further heterolytically split H···H into immobile H^‒ attached on the acidic centers of Ni−Ru/HZSM-5 and relatively mobile H⁺. Catalytic hydro-conversion of the extraction residue from Naomaohu lignite was further examined over the optimized catalyst, Ni−Ru/HZSM-5. Detailed molecular compositions of products from the extraction residue with and without hydrogenation were characterized by Fourier transform infrared spectroscopy and gas chromatography/mass spectrometry. The analytical results showed that the oxygen-containing functional groups in products of hydrogenated extraction residue were obviously reduced after the catalytic treatment. The relative content of oxygenates in the product with catalytic treatment was 18.57% lower than that in the product without catalytic treatment.

关键词： HZSM-5 Ni-based catalyst catalytic hydrogenation coal model compound

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Digital image correlation-based structural state detection through deep learning

《结构与土木工程前沿（英文）》 2022年第16卷第1期页码 45-56 doi: 10.1007/s11709-021-0777-x

摘要： This paper presents a new approach for automatical classification of structural state through deep learning. In this work, a Convolutional Neural Network (CNN) was designed to fuse both the feature extraction and classification blocks into an intelligent and compact learning system and detect the structural state of a steel frame; the input was a series of vibration signals, and the output was a structural state. The digital image correlation (DIC) technology was utilized to collect vibration information of an actual steel frame, and subsequently, the raw signals, without further pre-processing, were directly utilized as the CNN samples. The results show that CNN can achieve 99% classification accuracy for the research model. Besides, compared with the backpropagation neural network (BPNN), the CNN had an accuracy similar to that of the BPNN, but it only consumes 19% of the training time. The outputs of the convolution and pooling layers were visually displayed and discussed as well. It is demonstrated that: 1) the CNN can extract the structural state information from the vibration signals and classify them; 2) the detection and computational performance of the CNN for the incomplete data are better than that of the BPNN; 3) the CNN has better anti-noise ability.

关键词： structural state detection deep learning digital image correlation vibration signal steel frame

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Development of temperature-robust damage factor based on sensor fusion for a wind turbine structure

Jong-Woong PARK,Sung-Han SIM,Jin-Hak YI,Hyung-Jo JUNG

《结构与土木工程前沿（英文）》 2015年第9卷第1期页码 42-47 doi: 10.1007/s11709-014-0285-3

摘要： Wind power systems have gained much attention due to the relatively high reliability, maturity in technology and cost competitiveness compared to other renewable alternatives. Advances have been made to increase the power efficiency of the wind turbines while less attention has been focused on structural integrity assessment of the structural systems. Vibration-based damage detection has widely been researched to identify damages on a structure based on change in dynamic characteristics. Widely spread methods are natural frequency-based, mode shape-based, and curvature mode shape-based methods. The natural frequency-based methods are convenient but vulnerable to environmental temperature variation which degrades damage detection capability; mode shapes are less influenced by temperature variation and able to locate damage but requires extensive sensor instrumentation which is costly and vulnerable to signal noises. This study proposes novelty of damage factor based on sensor fusion to exclude effect of temperature variation. The combined use of an accelerometer and an inclinometer was considered and damage factor was defined as a change in relationship between those two measurements. The advantages of the proposed method are: 1) requirement of small number of sensor, 2) robustness to change in temperature and signal noise and 3) ability to roughly locate damage. Validation of the proposed method is carried out through numerical simulation on a simplified 5 MW wind turbine model.

关键词： sensor fusion damage detection structural health monitoring

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Asymmetric transfer hydrogenation of prochiral ketone catalyzed over Fe-CS/SBA-15 catalyst

XUE Ping, WU Tao

《化学科学与工程前沿（英文）》 2007年第1卷第3期页码 251-255 doi: 10.1007/s11705-007-0045-1

摘要： A heterogeneous chiral catalyst Fe(III)-CS (chitosan) complex/mesoporous molecular sieve SBA-15 (Santa Barbara Amorphous) was prepared. The asymmetric transfer hydrogenations of prochiral acetophenone and 4-methyl-2-pentanone to corresponding chiral alcohols were carried out on Fe-CS/SBA-15 at atmosphere pressure using 2-propanol as hydrogen donor. Effects of Fe content in catalyst, reaction temperature, reaction time and promoter KOH concentration on the conversion of substrates and enantioselectivity were investigated. Fe-CS/SBA-15 with 2.2% mass fraction Fe exhibits considerable enantioselectivity and catalytic activity for the asymmetric transfer hydrogenations of aromatic ketone and aliphatic ketone. Under optimal reaction conditions: KOH concentration 0.03 mol/L, reaction temperature 70ºC and reaction time 4 h, enantiomer excess (ee) of ()-1-phenylethanol and conversion of acetophenone can reach 87.4% and 27.7%, respectively. Under the above KOH concentration and reaction temperature and reaction time of 8 h, the ee of ()-4-methyl-2-pentanol and conversion 4-methyl-2-pentanone amounted to 50.2% and 25.5%, respectively.

关键词： asymmetric transfer enantioselectivity Fe-CS/SBA-15 aliphatic aromatic

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Application of a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for EdgeDetection in Image Processing

《机械工程前沿（英文）》 2006年第1卷第1期页码 85-89 doi: 10.1007/s11465-005-0023-6

摘要：

A novel fuzzy clustering method based on chaos immune evolutionary algorithm (CIEFCM) is presented to solve fuzzy edge detection problems in image processing. In CIEFCM, a tiny disturbance is added to a filial generation group using a chaos variable and the disturbance amplitude is adjusted step by step, which greatly improves the colony diversity of the immune evolution algorithm (IEA). The experimental results show that the method not only can correctly detect the fuzzy edge and exiguous edge but can evidently improve the searching efficiency of fuzzy clustering algorithm based on IEA.

关键词： disturbance amplitude disturbance diversity generation processing

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一种基于粗糙集的模糊信息融合方法及应用

陈双叶,张微敬

《中国工程科学》 2006年第8卷第12期页码 75-79

摘要：

将粗糙集理论和模糊逻辑技术结合起来，提出了一种基于粗糙集数据处理的模糊信息融合方法。运用粗糙集的基本理论和简约计算方法，从大量原始数据中发现精简的、概略化的规则，结合模糊逻辑推理建立一致粗糙模糊模型，并提出了对模型进行扩充与完备化的概念。脉动真空灭菌温度控制过程的仿真试验研究结果表明了所提方法的有效性和可行性。

关键词：信息融合粗糙集模糊逻辑粗糙模糊模型

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基于图块的局部加权表决标记融合分割算法 Article

Kai ZHU, Gang LIU, Long ZHAO, Wan ZHANG

《信息与电子工程前沿（英文）》 2017年第18卷第5期页码 680-688 doi: 10.1631/FITEE.1500457

摘要：标记融合是医学图像处理中越来越受欢迎的一种强大的图像分割策略。然而，同时满足高精度和快速分割却是对算法的一个极大的挑战。结合局部加权表决策略和贝叶斯推论，本文提出了一种新的基于图块的分割算法。通过ANTs（Advanced normalization tools）算法将训练图谱图像向目标图像进行配准，并将配准后的训练图谱标记映射到目标图像中来获得分割结果。首先在执行局部加权表决策略中将灰度先验概率和标记先验概率作为两个关键的指标，然后在图块水平上计算这两种先验概率。接着在分析标记融合的过程中，首次提出了把图像的背景区域作为单独的一个标记值来处理，再估算标记先验概率的方案。最后，利用Dice score作为评估分割精度的标准，将该算法分割的结果与其他一些方法进行了比较，如多数表决、局部加权表决、基于图块的多数表决以及广泛运用于整个大脑分割的工具FreeSurfer。实验结果证明本文提出的算法要优于其他分割方法。在实验中，本文还讨论了不同参数（包括图块大小、图块面积和训练图谱个数）对分割精度的影响。

关键词：标记融合；局部加权表决；基于图块；背景分析

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预腐蚀后拉伸超载对LC4CS铝合金疲劳性能的影响

蒋荟,杨晓华

《中国工程科学》 2006年第8卷第2期页码 44-46

摘要：

采用预腐蚀后进行单次拉伸超载疲劳试验的方法，研究了腐蚀与超载对LC4CS材料疲劳寿命的影响。

关键词： LC4CS 铝合金预腐蚀超载疲劳寿命