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THREE-DIMENSIONAL ANALYSIS OF FUNCTIONALLY GRADED PLATE BASED ON THE HAAR WAVELET METHOD 被引量:2
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作者 Zhang Chun Zhong Zheng 《Acta Mechanica Solida Sinica》 SCIE EI 2007年第2期95-102,共8页
A three-dimensional analysis of a simply-supported functionally graded rectangular plate with an arbitrary distribution of material properties is made using a simple and effective method based on the Haar wavelet. Wit... A three-dimensional analysis of a simply-supported functionally graded rectangular plate with an arbitrary distribution of material properties is made using a simple and effective method based on the Haar wavelet. With good features in treating singularities, Haar series solution converges rapidly for arbitrary distributions, especially for the case where the material properties change rapidly in some regions. Through numerical examples the influences of the ratio of material constants on the top and bottom surfaces and different material gradient distributions on the structural response of the plate to mechanical stimuli are studied. 展开更多
关键词 functionally graded material rectangular plate Haar wavelet three-dimensional analysis
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Classification of forearm action surface EMG signals based on fractal dimension 被引量:1
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作者 胡晓 王志中 任小梅 《Journal of Southeast University(English Edition)》 EI CAS 2005年第3期324-329,共6页
Surface electromyogram (EMG) signals were identified by fractal dimension.Two patterns of surface EMG signals were acquired from 30 healthy volunteers' right forearm flexor respectively in the process of forearm su... Surface electromyogram (EMG) signals were identified by fractal dimension.Two patterns of surface EMG signals were acquired from 30 healthy volunteers' right forearm flexor respectively in the process of forearm supination (FS) and forearm pronation (FP).After the raw action surface EMG (ASEMG) signal was decomposed into several sub-signals with wavelet packet transform (WPT),five fractal dimensions were respectively calculated from the raw signal and four sub-signals by the method based on fuzzy self-similarity.The results show that calculated from the sub-signal in the band 0 to 125 Hz,the fractal dimensions of FS ASEMG signals and FP ASEMG signals distributed in two different regions,and its error rate based on Bayes decision was no more than 2.26%.Therefore,the fractal dimension is an appropriate feature by which an FS ASEMG signal is distinguished from an FP ASEMG signal. 展开更多
关键词 action surface electrolnyogram (ASEMG) signal: fractal dimension wavelet packet transform(WPT) fuzzy self-similarity Bayes decision
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CONSTRUCTION OF COMPACTLY SUPPORTED BIVARIATE ORTHOGONAL WAVELETS BY UNIVARIATE ORTHOGONAL WAVELETS 被引量:4
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作者 杨建伟 李落清 唐远炎 《Acta Mathematica Scientia》 SCIE CSCD 2005年第2期233-242,共10页
After some permutation of conjugate quadrature filter, new conjugate quadrature filters can be derived. In terms of this permutation, an approach is developed for constructing compactly supported bivariate orthogonal ... After some permutation of conjugate quadrature filter, new conjugate quadrature filters can be derived. In terms of this permutation, an approach is developed for constructing compactly supported bivariate orthogonal wavelets from univariate orthogonal wavelets. Non-separable orthogonal wavelets can be achieved. To demonstrate this method, an example is given. 展开更多
关键词 PERMUTATION non-separable wavelets conjugate quadrature filter
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Texture image classification using multi fractal dimension 被引量:1
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作者 LIU Zhuo-fu and SANG En-fang School of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001 , China 《Journal of Marine Science and Application》 2003年第2期76-81,共6页
This paper presents a supervised classification method of sonar image, which takes advantages of both multi-fractal theory and wavelet analysis. In the process of feature extraction, image transformation and wavelet d... This paper presents a supervised classification method of sonar image, which takes advantages of both multi-fractal theory and wavelet analysis. In the process of feature extraction, image transformation and wavelet decomposition are combined and a feature set based on multi-fractal dimension is obtained. In the part of classifier construction, the Learning Vector Quantization (LVQ) network is adopted as a classifier. Experiments of sonar image classification were carried out with satisfactory results, which verify the effectiveness of this method. 展开更多
关键词 wavelet analysis multi-fractal dimension sonar image classification TEXTURE LVQ classifier
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Improved wavelet neural network combined with particle swarm optimization algorithm and its application 被引量:1
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作者 李翔 杨尚东 +1 位作者 乞建勋 杨淑霞 《Journal of Central South University of Technology》 2006年第3期256-259,共4页
An improved wavelet neural network algorithm which combines with particle swarm optimization was proposed to avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learnin... An improved wavelet neural network algorithm which combines with particle swarm optimization was proposed to avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learning ability brought about by the traditional models. Based on the operational data provided by a regional power grid in the south of China, the method was used in the actual short term load forecasting. The results show that the average time cost of the proposed method in the experiment process is reduced by 12.2 s, and the precision of the proposed method is increased by 3.43% compared to the traditional wavelet network. Consequently, the improved wavelet neural network forecasting model is better than the traditional wavelet neural network forecasting model in both forecasting effect and network function. 展开更多
关键词 artificial neural network particle swarm optimization algorithm short-term load forecasting wavelet curse of dimensionality
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WAVELET APPROXIMATE INERTIAL MANIFOLD AND NUMERICAL SOLUTION OF BURGERS' EQUATION
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作者 田立新 许伯强 刘曾荣 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2002年第10期1140-1152,共13页
The existence of approximate inertial manifold Using wavelet to Burgers' equation, and numerical solution under multiresolution analysis with the low modes were studied. It is shown that the Burgers' equation ... The existence of approximate inertial manifold Using wavelet to Burgers' equation, and numerical solution under multiresolution analysis with the low modes were studied. It is shown that the Burgers' equation has a good localization property of the numerical solution distinguishably. 展开更多
关键词 wavelet wavelet approximate inertial manifold (WAIM) wavelet Galerkin solution infinite dimensional dynamic system
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Wavelet-Aggregated Signal in Earthquake Prediction 被引量:1
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作者 A.A.Lyubushin Jr 《Earthquake Research in China》 1999年第1期35-45,共11页
The concept of aggregated signal is introduced. Quantitatively, an aggregated signal can be defined as the scalar signal: it accumulates in its own variations only those spectral components that are presented simultan... The concept of aggregated signal is introduced. Quantitatively, an aggregated signal can be defined as the scalar signal: it accumulates in its own variations only those spectral components that are presented simultaneously in each scalar time series of the multidimensional signal to be analyzed. Moreover, an algorithm of aggregation is proposed to suppress the spectral components that are present in any of the scalar components but absent in others (these components can be called local disturbance signals, for instance of technogenic nature). The main purpose of constructing the aggregated signal is to make clearer the common tendency of low-frequency data-flow in geophysical networks, which indicates an increase in collective behavior.It is known that almost all models of the process of earthquake preparation have pointed out an increase in collective behavior of components of geophysical fields in the region of preparation when the coming geocatastrophe has entered its long- and mid-term stages. 展开更多
关键词 MULTI-dimensional time series analysis aggregated SIGNALS wavelets.
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On Wavelet Transform General Modulus Maxima Metric for Singularity Classification in Mammograms
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作者 Tomislav Bujanovic Ikhlas Abdel-Qader 《Open Journal of Medical Imaging》 2013年第1期17-30,共14页
Continuous wavelet transform is employed to detect singularities in 2-D signals by tracking modulus maxima along maxima lines and particularly applied to microcalcification detection in mammograms. The microcalcificat... Continuous wavelet transform is employed to detect singularities in 2-D signals by tracking modulus maxima along maxima lines and particularly applied to microcalcification detection in mammograms. The microcalcifications are modeled as smoothed positive impulse functions. Other target property detection can be performed by adjusting its mathematical model. In this application, the general modulus maximum and its scale of each singular point are detected and statistically analyzed locally in its neighborhood. The diagnosed microcalcification cluster results are compared with health tissue results, showing that general modulus maxima can serve as a suspicious spot detection tool with the detection performance no significantly sensitive to the breast tissue background properties. Performed fractal analysis of selected singularities supports the statistical findings. It is important to select the suitable computation parameters-thresholds of magnitude, argument and frequency range-in accordance to mathematical description of the target property as well as spatial and numerical resolution of the analyzed signal. The tests are performed on a set of images with empirically selected parameters for 200 μm/pixel spatial and 8 bits/pixel numerical resolution, appropriate for detection of the suspicious spots in a mammogram. The results show that the magnitude of a singularity general maximum can play a significant role in the detection of microcalcification, while zooming into a cluster in image finer spatial resolution both magnitude of general maximum and the spatial distribution of the selected set of singularities may lead to the breast abnormality characterization. 展开更多
关键词 Continuous wavelet Transform Fractal dimension GENERAL MODULUS Maximum MICROCALCIFICATION SINGULARITY Smoothed IMPULSE Function
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Very Low Bit-Rate Video Coding by Combining H.264/AVC Standard and 2-D Discrete Wavelet Transform
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作者 Ali Aghagolzadeh Saeed Meshgini +1 位作者 Mehdi Nooshyar Mehdi Aghagolzadeh 《Wireless Sensor Network》 2010年第4期328-336,共9页
In this paper, we propose a new method for very low bit-rate video coding that combines H.264/AVC standard and two-dimensional discrete wavelet transform. In this method, first a two dimensional wavelet transform is a... In this paper, we propose a new method for very low bit-rate video coding that combines H.264/AVC standard and two-dimensional discrete wavelet transform. In this method, first a two dimensional wavelet transform is applied on each video frame independently to extract the low frequency components for each frame and then the low frequency parts of all frames are coded using H.264/AVC codec. On the other hand, the high frequency parts of the video frames are coded by Run Length Coding algorithm, after applying a threshold to neglect the low value coefficients. Experiments show that our proposed method can achieve better rate-distortion performance at very low bit-rate applications below 16 kbits/s compared to applying H.264/AVC standard directly to all frames. Applications of our proposed video coding technique include video telephony, video-conferencing, transmitting or receiving video over half-rate traffic channels of GSM networks. 展开更多
关键词 Video CODING H.264/AVC STANDARD RUN Length CODING Two-dimensional wavelet Transform
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小样本下基于DWT和2D-CNN的齿轮故障诊断方法 被引量:1
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作者 宋庭新 黄继承 +2 位作者 刘尚奇 杜敏 李子平 《计算机集成制造系统》 北大核心 2025年第6期2206-2214,共9页
针对齿轮设备运维过程中故障信号较少的情况,提出一种将离散小波变换(DWT)与二维卷积神经网络(2D-CNN)相结合的故障识别方法。该方法通过将少量信号经卷积神经网络得到的分类标签与信号的小波能量进行权值分配,实现对齿轮的故障识别。... 针对齿轮设备运维过程中故障信号较少的情况,提出一种将离散小波变换(DWT)与二维卷积神经网络(2D-CNN)相结合的故障识别方法。该方法通过将少量信号经卷积神经网络得到的分类标签与信号的小波能量进行权值分配,实现对齿轮的故障识别。为了充分获取小样本中的信息来训练神经网络,利用离散小波分解、图像变换和Markov变迁场方法对样本信号进行增量和转换。通过验证齿轮箱数据集得到96%的训练准确率和87.5%的分类准确率,同时通过消融实验和对比实验证明,该方法可以有效克服小样本数据中的噪声干扰,使数据得到增强,在齿轮故障识别中具有很好的现实意义。 展开更多
关键词 故障诊断 小样本 二维卷积神经网络 小波变换
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基于GASF与MSCAM-DenseNet的小样本齿轮故障诊断方法 被引量:1
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作者 史丽晨 张鹏 +1 位作者 王海涛 周星宇 《计算机集成制造系统》 北大核心 2025年第8期3033-3045,共13页
针对小样本条件下所得样本不足,特征未能有效提取导致诊断精度下降的问题,提出一种GASF与MSCAM-DenseNet相结合的小样本齿轮故障诊断方法。首先,运用格拉姆角和域(GASF)将多源振动信号变换为二维特征,采用二维离散小波变换(2D-DWT)重构... 针对小样本条件下所得样本不足,特征未能有效提取导致诊断精度下降的问题,提出一种GASF与MSCAM-DenseNet相结合的小样本齿轮故障诊断方法。首先,运用格拉姆角和域(GASF)将多源振动信号变换为二维特征,采用二维离散小波变换(2D-DWT)重构多源特征。其次,由于一般的密集连接卷积网络(DenseNet)不具备识别多尺度特征的能力,因而在DenseNet中引入多尺度通道注意力机制(MSCAM),提出一种改进网络模型,即MSCAM-DenseNet。最后,以重构后的GASF作为MSCAM-DenseNet的输入,待特征识别完成后,由网络分类器完成故障特征分类。采用实验室行星齿轮数据集和东南大学齿轮箱数据集对所提模型验证,并与其他诊断模型进行对比。实验结果证明,所提方法在小样本、变工况条件下具有较高的故障识别准确率,较强的泛化能力和抗噪能力。 展开更多
关键词 齿轮 小样本故障诊断 格拉姆角和域 二维离散小波变换 多尺度通道注意力机制
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基于RPM和多任务学习的表面加工质量预测
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作者 史丽晨 田贺元 +1 位作者 豆卫涛 杨洁 《制造业自动化》 2025年第10期29-42,共14页
针对实际制造过程中需要同时在线监测多个表面加工质量评价指标的问题,提出一种基于RPM和MTL-GAMDenseNet-CA网络的表面粗糙度识别及尺寸精度预测方法。首先,通过RPM对多通道振动信号进行二维转换,得到相应的二维RPM图,再利用二维离散... 针对实际制造过程中需要同时在线监测多个表面加工质量评价指标的问题,提出一种基于RPM和MTL-GAMDenseNet-CA网络的表面粗糙度识别及尺寸精度预测方法。首先,通过RPM对多通道振动信号进行二维转换,得到相应的二维RPM图,再利用二维离散小波变换对多通道RPM图进行分解重构;其次,将GAM注意力机制引入到DenseNet模型中,构成新的GAMDenseNet网络作为模型的编码器,再将CA注意力机制融入到解码器结构中,利用硬参数共享网络架构构建MTL-GAMDenseNet-CA多任务学习网络模型;并通过梯度归一化算法(GradNorm)自适应调整表面粗糙度识别和尺寸精度预测两个任务损失函数的权重比例,对模型进行优化;最后通过对比实验及消融实验,对所提方法进行验证。实验结果表明:在表面粗糙度识别任务中,该方法的准确率达到了99.88%;在尺寸精度预测任务中的平均绝对误差(MAE)和均方根误差(RMSE)分别达到了0.0177和0.0221。这表明所提方法能够有效实现表面加工质量多评价指标的在线监测。 展开更多
关键词 多任务学习 表面粗糙度 相对位置矩阵 二维离散小波变换 尺寸精度预测
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融合DB4小波变换的放射源特征峰提取方法
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作者 王超亚 瞿金辉 +6 位作者 李浪 袁恺鸣 陈步龙 汤斌 王少飞 赵明富 宋涛 《重庆理工大学学报(自然科学)》 北大核心 2025年第8期222-228,共7页
核素的识别在放射源定位中起着极其重要的作用,而在核素识别中,γ能谱的寻峰方法又是核素识别的基础,寻峰的灵敏度和准确性决定了最终核素识别方法的性能。提出一种基于小波变换的放射源特征峰提取方法,通过实测谱数据和G1200谱线数据... 核素的识别在放射源定位中起着极其重要的作用,而在核素识别中,γ能谱的寻峰方法又是核素识别的基础,寻峰的灵敏度和准确性决定了最终核素识别方法的性能。提出一种基于小波变换的放射源特征峰提取方法,通过实测谱数据和G1200谱线数据作为实验验证依据,利用小波变换结合二维方差阈值方法在初始数据中建立客观的寻峰标准。实验结果表明,运用该方法在G1200寻峰算法评测谱上的漏寻率比ORTEC软件降低约13.63%,可以有效避开康普顿边,具有实际部署的潜力。 展开更多
关键词 特征峰 G1200谱线 小波变换 二维方差
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面向高维异常数据挖掘的小波变换算法优化 被引量:2
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作者 陈玲萍 杨呈永 《计算机仿真》 2025年第1期462-465,472,共5页
为深度挖掘高维异常数据,获取准确数据信息,提出一种基于小波变换优化算法。利用小波变换算法充分挖掘数据的时空频率和变化特点,区分出低频和高频序列。判断数据异常值的真伪,确定挖掘极值对应的阈值区间,补全参数序列,滤除掉数据时频... 为深度挖掘高维异常数据,获取准确数据信息,提出一种基于小波变换优化算法。利用小波变换算法充分挖掘数据的时空频率和变化特点,区分出低频和高频序列。判断数据异常值的真伪,确定挖掘极值对应的阈值区间,补全参数序列,滤除掉数据时频残差中噪声,测算傅里叶变换函数的时频序列,利用遗传算法优化小波变换,使算法能同时处理群体中的多个数据,获取异常数据挖掘的全局最优解,并确定数据位置与核心距离,完成高维异常数据的挖掘和判断。经实验证明所提优化后小波变换算法能有效挖掘并识别出高维异常数据,描述样本数据的变化波动,降低数据挖掘误差。 展开更多
关键词 高维异常数据 数据挖掘 小波变换 遗传算法
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基于球面DOG小波框架的骨料形状重构研究
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作者 李景哲 高鹏 +3 位作者 詹炳根 胡焱博 沙慧玲 余其俊 《工程力学》 北大核心 2025年第6期195-202,共8页
基于高斯差分小波(Difference of Gaussians,DOG)向球面上拓展产生的球面DOG小波函数,提出了基于球面DOG小波框架重构骨料形状的新方法。为探讨该方法的优势,采用该方法和传统球谐重构法,对采用三维扫描仪获取机制砂的表面点云数据进行... 基于高斯差分小波(Difference of Gaussians,DOG)向球面上拓展产生的球面DOG小波函数,提出了基于球面DOG小波框架重构骨料形状的新方法。为探讨该方法的优势,采用该方法和传统球谐重构法,对采用三维扫描仪获取机制砂的表面点云数据进行重构,分析了球面DOG小波框架方法的参数设置,以及准确性。结果显示,随着球面DOG小波框架qmax的增大,重构骨料的形貌逐渐接近真实形态。且当qmax达到4时,支撑集足够小的球面DOG小波可有效避免高阶次球谐级数重构多棱角骨料时由于振铃效应导致的重构精度下降问题。 展开更多
关键词 球面DOG小波框架 球谐函数 三维扫描 机制砂 颗粒形状
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双域多尺度特征提取的轨道面瑕疵检测算法
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作者 胡贺南 都业辉 +2 位作者 李荣华 王大志 张然 《铁道科学与工程学报》 北大核心 2025年第9期4218-4233,共16页
轨道面瑕疵检测是保障铁路系统安全运行的关键技术。针对现有的轨道面瑕疵检测算法存在准确率低和漏检率高的问题,基于YOLOv5s框架,提出一种双域多尺度特征提取的轨道面瑕疵检测算法。首先,设计动态增强上采样模块,减少上采样过程中导... 轨道面瑕疵检测是保障铁路系统安全运行的关键技术。针对现有的轨道面瑕疵检测算法存在准确率低和漏检率高的问题,基于YOLOv5s框架,提出一种双域多尺度特征提取的轨道面瑕疵检测算法。首先,设计动态增强上采样模块,减少上采样过程中导致的分辨率损失和伪影现象,提升对轨道面瑕疵细粒度特征的获取能力;其次,提出自协同卷积块注意力,结合自注意力机制和卷积块注意力机制的优势,在捕获轨道面瑕疵全局上下文信息的同时,抑制无用背景信息的干扰;随后,采用全维动态卷积替换主干网络中的标准卷积,动态调整卷积核参数,实现对轨道面瑕疵的多尺度特征提取;最后,构建小波变换金字塔模块,通过Haar小波分解,联合提取瑕疵的空间域和频域特征,增强全局形状建模与细节表达能力。实验结果表明,各改进策略均有效提升了模型的检测性能。在自建的轨道面瑕疵数据集上,改进算法的平均精度mAP_(50)和mAP_(50-95)分别达到84.4%和53.3%,GFLOPs为13.8G,相比于YOLOv5s,平均精度mAP50和mAP_(50-95)分别提升4.6个百分点和6.7个百分点,GFLOPs降低13.8%。与Faster R-CNN、RT-DETR、SSD、YOLOv7等主流目标检测算法以及其他轨道面瑕疵检测算法相比,改进算法具有更高的检测精度,同时在公开的轨道面瑕疵数据集上展现出良好的泛化能力,证明了其在轨道面瑕疵检测领域的有效性。 展开更多
关键词 轨道面瑕疵检测 上采样模块 注意力机制 全维动态卷积 小波变换
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Multi-spectral image fusion method based on two channels non-separable wavelets 被引量:9
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作者 LIU Bin1,2 & PENG JiaXiong3 1 School of Mathematics and Computer Science, Hubei University, Wuhan 430062, China 2 Key Laboratory of Applied Mathematics of Hubei Province, Wuhan 430062, China 3 Institute of Image Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan 430074, China 《Science in China(Series F)》 2008年第12期2022-2032,共11页
A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1,-1] and its application in the fusion of multi-spectral image are presented. Many 4×4 filter banks are de... A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1,-1] and its application in the fusion of multi-spectral image are presented. Many 4×4 filter banks are designed. The multi-spectral image fusion algorithm based on this kind of wavelet is proposed. Using this filter bank, multi-resolution wavelet decomposition of the intensity of multi-spectral image and panchromatic image is performed, and the two low-frequency components of the intensity and the panchromatic image are merged by using a tradeoff parameter. The experiment results show that this method is good in the preservation of spectral quality and high spatial resolution information. Its performance in preserving spectral quality and high spatial information is better than the fusion method based on DWFT and IHS. When the parameter t is closed to 1, the fused image can obtain rich spectral information from the original MS image. The amount of computation reduced to only half of the fusion method based on four channels wavelet transform. 展开更多
关键词 image fusion non-separable wavelets multi-spectral image panchromatic image
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N DIMENSIONAL FINITE WAVELET FILTERS 被引量:3
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作者 Si-long Peng (NADEC, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China) 《Journal of Computational Mathematics》 SCIE EI CSCD 2003年第5期595-602,共8页
In this paper, a large class of n dimensional orthogonal and biorthognal wavelet filters (lowpass and highpass) are presented in explicit expression. We also characterize orthogonal filters with linear phase in this c... In this paper, a large class of n dimensional orthogonal and biorthognal wavelet filters (lowpass and highpass) are presented in explicit expression. We also characterize orthogonal filters with linear phase in this case. Some examples are also given, including non separable orhogonal and biorthogonal filters with linear phase. 展开更多
关键词 n dimension Linear phase wavelet filters.
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Parameterization of 3-channel non-separable 2-D wavelets and filters 被引量:3
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作者 GAOXieping ZHONGHua 《Science in China(Series F)》 2004年第3期362-371,共10页
We propose a complete parameterization presentation of the 3-channelbivariate non-separable orthogonal FIR filter, and describe the sufficient condition ofgenerating continuous wavelet bases. Given the results above, ... We propose a complete parameterization presentation of the 3-channelbivariate non-separable orthogonal FIR filter, and describe the sufficient condition ofgenerating continuous wavelet bases. Given the results above, a non-separable,compactly supported, orthogonal, continuous parameterized bivariate wavelet bank is setup here. 展开更多
关键词 wavelet function FIR filter non-separable
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构造2D高斯复小波用于非均匀反射物面三维测量
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作者 张曼琦 陈文静 张启灿 《光学与光电技术》 2025年第1期86-98,共13页
得益于时频分析和多分辨特性,小波变换轮廓术(Wavelet Transform Profilometry,WTP)能从单帧条纹中高精度提取携带被测物面高度信息的相位图。小波变换轮廓术的相位解调难易程度和精度依赖于小波的选取。复小波可以直接用于条纹相位解... 得益于时频分析和多分辨特性,小波变换轮廓术(Wavelet Transform Profilometry,WTP)能从单帧条纹中高精度提取携带被测物面高度信息的相位图。小波变换轮廓术的相位解调难易程度和精度依赖于小波的选取。复小波可以直接用于条纹相位解调。一维高斯函数的n阶导数满足小波的容许条件,且任意边带的频谱分布具有平滑、非对称的特点。它们作为一维实小波基函数,结合2D复小波通用框架,可以用于构造方向性好、平滑且适合条纹分析的二维复小波,有效提高小波变换轮廓术的相位计算精度。通过理论分析和数字计算,详细说明了用一维高斯函数一阶、二阶和三阶导数分别构造的2D复小波空-频域特性,并将其应用于低信噪比和低对比度条纹分析以重建物面三维面形。以PMP结果作为参考值,平面测量时,所构造的三个2D高斯复小波三维面形重建误差的STD均小于0.07;非均匀反射物面测量时,采用构造小波的2D WTP解调存在低信噪条纹时,重建结果优于复墨西哥帽小波和传统Fan小波。在非暗场区域,重建误差的STD均小于0.05,有效提高了测量精度。研究工作丰富了2D WTP的小波基函数库,拓展了2D WTP在光学测量和条纹分析中的应用前景。 展开更多
关键词 结构光投影 三维面形测量 小波变换轮廓术 二维复小波 相位计算
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