基于连续小波变换的简正波检测与提取技术

宽带声源在远距离传播中的频散过程反映着海洋环境特性的重要信息,准确提取这一过程中各简正波的有关信息是有效实现海洋声场反演的重要前提。小波变换虽然已被用于获取宽带声源的时频分布,但不具备适用于不同信号的柔性。在此背景下,本文介绍了一种自适应基小波方法,可适应不同形式的爆炸声信号,从而有效实现了频散现象的获取。在此基础上,本文同时建立了各号简正波的重构方法,经仿真测试,重构出的简正波与实际波形几乎相同。     

基于最小各向同性小波滤波的图像清晰度识别

提出了基于最小各向同性小波滤波的图像清晰度识别方法,对二维最小各向同性小波滤波提取图像特征进行了研究.直接将原始图像通过带通小波滤波器G0获得图像边缘信息,结合图像能量分析,建立了基于小波滤波的图像清晰度评价函数.利用构建的显微镜自动对焦实验平台,比较分析了基于小波滤波和拉普拉斯的评价方法.实验结果表明,采用基于各向同性小波滤波的自动对焦算法有更好的综合自动对焦性能.     

Extended fractional wavelet joint transform correlator

An extended fractional wavelet joint transform correlator is implemented for real-time target recognition applications. The real-time input scene captured using a charge-coupled device camera along with the reference image is fractional Fourier transformed. The obtained joint power spectrum is multiplied by an appropriately scaled wavelet filter and the resultant function is differentiated. The application of wavelet filter enhances the correlation outputs and differential processing of wavelet-filtered joint power spectrum improves the detection efficiency by reducing the zero-order spectra. Targets with Gaussian and speckle noise have also been used to check the correlation output. The performance metrics: correlation peak intensity, peak-to-correlation energy, peak-to-sidelobe ratio and signal to clutter ratio have been calculated. The experimental results are presented in support of the proposed idea.     

基于小波变换的分水岭图像分割方法

图像分割技术在数字图像处理中占有重要地位.提出了一种基于小波变换的图像分割方法,有效地将小波分析、小波包分解与数学形态学中的分水岭方法相结合.首先,通过小波包对图像有效降噪,在一定程度上减少了分水岭方法的过分割现象.然后利用小波变换得到的梯度向量进行分水岭变换,有效保持边缘信息.实验结果证明该算法是可行的,与基于形态梯度的分割结果相比,得到了较好的分割效果.     

Wavelet transform implementation by layers

I.IntroductionWavelettheoryanditsapplicationhavebeendevelopedquicklyformallyyears,whichcoverquitealargeareaandprovideverygeneraltechniquesthatcanbeaPpliedtomanytasksinsignalprocessing,andhavenumerouspotelltialapplications.lnacousticresearchthereisatra-ditionofthefrequencyanalysisintermsofoctave,whichfitstheconceptof"constantQ"inwavelettransform,e.g.thepowerspectrumofmusicismeasuredintermsof1/3octave.Sofartheimplemelltationofwavelettransformha-sbeendevelopedonlyforoneoctave,e.g.themultiresolut…     

基于连续小波变换的神经网络人脸识别研究

研究了基于连续小波变换的神经网络进行人脸识别的方法.介绍了小波分析的理论基础，详细讨论了根据小波变换系数的范数选取小波母函数的方法，根据小波脊线确定网络神经元个数的方法以及神经网络的初始化和参数训练方法.通过对人脸图像灰度的连续小波分析，神经网络的自组织自学习能力，调整连接权值和小波神经元的尺度、位移参数，完成人脸识别的任务.实验结果验证了该神经网络的识别性能明显优于用特征脸方法对相同人脸库进行的识别.     

基于小波变换的水果糖度近红外光谱检测研究

利用小波变换滤波技术对90个水果样品的近红外光谱信号进行了去噪处理,并结合滤波后重构光谱信号对水果糖度进行逐步线性回归(SMLR)建立其校正模型,通过34个样品的外部检验对校正模型精度进行评价。研究结果表明: 校正模型的预测精度在小波尺度为3时其预测精度最好,预测集的决定系数由原来的0.84提高到0.85, 预测集相对标准误差由原来的6.1% 降为6.0%。因此,使用小波去噪方法有消除原始光谱噪声作用,从而使最终的SMLR模型更具有代表性和稳健性,也提高了品质检测时模型预测精度。     

一种用于管道泄漏声定位的可调Q因子小波变换分析方法

针对泄漏声发射信号的非平稳随机特性,进行了泄漏声信号可调Q因子小波变换(Tunable Q-Factor Wavelet Transform,TQWT)的理论分析和实验研究。首先通过对典型泄漏声信号的TQWT分析,研究品质因子和分解尺度对泄漏声特征提取的影响。然后根据峭度最大原则,优选出适合泄漏声信号分析的TQWT参数。在此基础上,提出了一种基于TQWT提取管道泄漏声特征分量的方法,并将提取的特征分量进行互相关分析用于管道泄漏定位。实验结果表明,利用该方法可以有效提取出泄漏声信号中的特征分量,从而更好实现泄漏定位,定位误差较小。该项研究工作为实际工程管道泄漏检测提供了可行的解决方案。      

太阳射电爆发中图像网纹消除的小波NeighShrink方法

绝大多数观测得到的太阳爆发数据中均含有大量的噪声,这给数据的后续处理带来极大的困难。文章分析和研究了NeighShrink阈值函数的特点以及邻域窗口大小的选择依据,在此基础上提出了一种新的小波NeighShrink平方根阈值方法用于图像去噪。首先对太阳爆发灰度图中的每一通道作了规范化处理,在一定程度上去除由于通道间的差异造成的横条纹,然后将预处理后的图像进行小波分解,采用小波Neigh-Shrink平方根阈值函数对其小波系数作阈值处理,最后利用小波反变换恢复图像。实验结果表明该方法可以有效地实现去除干扰、增强有用信息的目的。     

Wavelet-modified fringe-adjusted joint transform correlator

In this paper, we implement a wavelet-modified fringe-adjusted joint transform correlator (JTC) for real-time target recognition applications. In real-time situation the input scene is captured using a charge-coupled device (CCD) camera. The obtained joint power spectrum is multiplied by a pre-synthesized fringe-adjusted filter and the resultant function is processed with an appropriately scaled wavelet filter. Three performance measure parameters: correlation peak intensity, peak-to-sidelobe ratio, and signal-to-clutter ratio have been calculated for fringe-adjusted joint transform correlator (FJTC) and wavelet-modified fringe-adjusted joint transform correlator (WFJTC). The WFJTC has been found to yield better results in comparison to conventional FJTC. To suppress the undesired strong dc, the resultant function is differentiated. Differential processing wavelet-modified fringe-adjusted joint power spectrum removes the zero-order spectra and hence improves the detection efficiency. To focus the correlation terms in different planes in order to capture one of the desired autocorrelation peaks and discard the strong dc and another autocorrelation peak, chirp-encoding technique has also been applied. Targets with Gaussian and speckle noise have also been used to check the correlation outputs. Computer simulation and experimental results are presented.     

Extraction of object position from in-line holograms by using single wavelet coefficient

A novel digital method for tracking position of objects from in-line holograms by using single wavelet coefficient is proposed. In the proposed method, a wavelet transform is used to analyze the holograms. An axial position of the object being studied is determined by using a real value of a resultant wavelet coefficient appears at a center position of interference fringes. A feasibility of this method is experimentally verified by analyzing holograms of an optical fiber.     

A new wavelet transform for reliability-guided phase unwrapping of optical fringe patterns

A new daughter wavelet definition for reliability-guided phase unwrapping of the optical fringe pattern is introduced. The new daughter wavelet definition is given by normalized mother wavelet with a new factor including a Gaussian function. The modulus of the wavelet transform coefficients, obtained by using daughter wavelet under this new daughter wavelet definition, includes not only modulation information but also local frequency information of the deformed fringe pattern. Therefore, it can be treated as a good parameter which represents the reliability of the reconstructed phase data. Mathematical demonstration of this parameter is given. Both the computer simulation and experiment reveal the validity of the proposed method.     

Wavelet analysis of digital shearing speckle patterns with a temporal carrier

Shearography is an optical technique allows direct measurement of deflection derivatives. This paper presents a novel temporal phase analysis technique based on wavelet transform when shearography is applied to measure a continuously deforming object. A series of shearing speckle patterns is captured by a high-speed camera during the deformation. To avoid the phase ambiguity problem, a temporal carrier is generated by a piezoelectrical transducer (PZT) stage in one beam of the modified Michelson interferometer. The intensity variation of each pixel on recorded images is then analyzed along time axis by a robust mathematical tool - complex Morlet wavelet transform. After the temporal carrier is removed, the absolute phase change representing the first-order derivative of the continuous deformation is obtained without the need of temporal or spatial phase unwrapping process. The results obtained by wavelet transform are compared with those from temporal Fourier transform.     

Improved holographic particle sizing by using absolute values of the wavelet transform

A new method for sizing particle from in-line particle holograms by using absolute values of the wavelet transform is proposed in order to improve accuracy in measurements. The proposed method provides direct calculation of the particle size by using spatial frequency information of a chirp signal at minima position of an envelope function. Simulation and experimental results are presented.     

Analysis on accuracy improvement of rotor–stator rubbing localization based on acoustic emission beamforming method

This paper attempts to introduce an improved acoustic emission (AE) beamforming method to localize rotor–stator rubbing fault in rotating machinery. To investigate the propagation characteristics of acoustic emission signals in casing shell plate of rotating machinery, the plate wave theory is used in a thin plate. A simulation is conducted and its result shows the localization accuracy of beamforming depends on multi-mode, dispersion, velocity and array dimension. In order to reduce the effect of propagation characteristics on the source localization, an AE signal pre-process method is introduced by combining plate wave theory and wavelet packet transform. And the revised localization velocity to reduce effect of array size is presented. The accuracy of rubbing localization based on beamforming and the improved method of present paper are compared by the rubbing test carried on a test table of rotating machinery. The results indicate that the improved method can localize rub fault effectively.     

星系光谱的400.0 nm跳变点的自动测量技术

本文给出星系光谱中的400.0nm跳变点位置和跳变值的自动测量方法,利用小波变换和离散卷积等技术,避免了对每条光谱进行繁琐的测量,可以作为星系光谱研究的预处理步骤。     

运用小波变换对遥感FTIR光谱进行信息提取

主要描述了如何利用小波变换技术,对一些强度较弱和混叠干扰的遥感FTIR光谱图进行信息提取。采用了墨西哥帽函数(Mexican hat function)小波,对三氯甲烷、丙酮的标准谱图及其两者混合物的遥感谱图信号进行了连续小波变换。结果发现,尺度越小,小波系数模的极大值点与突变点位置的对应就越准确。但小尺度下,小波系数由于受噪声影响,往往只凭一个尺度不能定位突变点的位置。相反,在大尺度下,对噪声进行了一定的平滑,极值点相对稳定,但由于平滑又会使定位产生偏差。因此,在用小波变换模极大值法判断信号突变点时,需要把多尺度结合起来综合观察。总之,小波分析技术能够较准确地、稳定地定位信号突变点,提取信息,并且具有平滑和放大有用信号的作用。对于非严重重叠的混合遥感光谱,根据对不同尺度下的小波变换系数的模极大值及其定位的分析,也可较好地识别谱图。     

Calculation of Refractive Index Changes from Thermal Lens Fringes using Continuous Wavelet Algorithm

Thermal lens fringes are obtained on the nile-blue/ethanol solution by illuminating it with a He–Ne laser in a Mach–Zehnder interferometer. The refractive index change distribution of these fringes is calculated by using two different continuous wavelet transform (CWT) algorithms. It is concluded that the CWT-phase method works better than the CWT-gradient algorithm for the analysis of thermal lens fringes according to theoretical results.     

基于WT算法联合混沌理论的图像加密研究

图像加密作为信息加密领域的重要一支,其对于信息安全的重要性显得愈发重要,能够有效地对目标图像信息进行加解密逐步成为了人们的研究热点。为了提高图像加密的安全性,以混沌系统所具有的初值敏感性以及类似随机为基础,提出了采用“混沌变换”方法对图像进行置乱操作的算法,随后以此为基础结合小波理论设计一种图像加密算法。在图像的预处理阶段首先对图像采用小波变换得到四幅小波子图;随后基于混沌置换将四幅子图置乱处理;最后通过小波逆变换恢复出目标加密图像。通过数值仿真实验表明通过该方法解密获得的图像具有与原图像非常高的一致性,并且获得了较高的安全性。     

A WAVELET TRANSFORM AND ITS APPLICATION TO SPECTROSCOPIC ANALYSIS

ABSTRACT

An introduction to the wavelet transform and its applications in spectroscopy analysis are presented. Owing to the property of the dual localization both in time and in frequency domains, the wavelet transform exhibits several useful characteristics. With the wavelet transform a signal can be decomposed into series of contributions according to the frequency difference, these contributions are respectively called discrete approximations and discrete details. By applying certain treatment to the discrete approximations (the low frequency part) or the discrete details (the high frequency part), a part of the original signal within a certain frequency range can be obtained. The wavelet transform has been applied in various fields of the analytical chemistry, including removal of high frequency noise, information extraction, resolution of overlapping signals, and data compression etc. Research concerning application in analytical chemistry are introduced in respect of photoacoustic spectroscopy, EXAFS spectrum, NMR analysis, and Raman spectrum.