Demodulation of a single interferogram based on continuous wavelet transform and phase derivative

A novel method based on continuous wavelet transform (CWT) and guidance of phase derivative is developed to measure the phase of a single fringe pattern which contains closed fringes. Wrapped phase values are retrieved by ridge extraction algorithms based on CWT which has the capability of better noise reduction and thus increases the resolution of measurement significantly. To further reduce the noise, the scales detected by maximum ridge algorithm are filtered iteratively before retrieval of wrapped phase. The proposed method also identifies any ambiguous point in a non-monotonous fringe pattern by directly tracking an inflexion point from an unwrapped phase map without the use of a carrier. The algorithm developed is validated by computer simulation and experimental results. Based on micro interferometry the experimental results for both static and dynamic deformations of a micro structure demonstrate that the proposed method is an effective tool for the analysis of closed fringe patterns and subsequent deformation measurement. However, the proposed technique is limited to measurement of surface which is relatively smooth compared to the mean wavelength of the light source. In addition, prior knowledge of the sign of surface slope is required in cases where a spatial carrier is not available or adaptable.     

Modal identification based on Gaussian continuous time autoregressive moving average model

A new time-domain modal identification method of the linear time-invariant system driven by the non-stationary Gaussian random force is presented in this paper. The proposed technique is based on the multivariate continuous time autoregressive moving average (CARMA) model. This method can identify physical parameters of a system from the response-only data. To do this, we first transform the structural dynamic equation into the CARMA model, and subsequently rewrite it in the state-space form. Second, we present the exact maximum likelihood estimators of parameters of the continuous time autoregressive (CAR) model by virtue of the Girsanov theorem, under the assumption that the uniformly modulated function is approximately equal to a constant matrix over a very short period of time. Then, based on the relation between the CAR model and the CARMA model, we present the exact maximum likelihood estimators of parameters of the CARMA model. Finally, the modal parameters are identified by the eigenvalue analysis method. Numerical results show that the method we introduced here not only has high precision and robustness, but also has very high computing efficiency. Therefore, it is suitable for real-time modal identification.     

Gabor transform and continuous wavelet transform for model pulsed signals

A model of a pulsed signal in the form of a superposition of elementary nonstationary signals is considered. The parameters of such a superposition are chosen so that signal amplitude A(t) strongly varies with time. For such a signal, the analytic expression for the Gabor transform (GT) and continuous wavelet transform (CWT) using the mother Morlet wavelet are analyzed. A criterion is proposed for the matched behaviors of GT and CWT with signal amplitude A(t). The advantages of the CWT adaptively selecting the window size over the GT whose explicit form depends on the window size are demonstrated. The proposed method can be used for analysis of many transient stages of time-dependent signals in various branches of physics.     

一种基于小波变换的跨带矢量量化

由小波变换产生的子带之间存在着较强的相关性,然而目前的在基于小波变换的图像编码矢量量化中,码矢往往仅由带内系数组成,没有充分利用带间相关性。本文提出一种新的跨带矢量量化算法,码矢由在同级子带中的相应系数组成。在三次小波变换下,第一级子带的码矢维数为４８Ｄ,第二级为１２Ｄ,第三级为３Ｄ。这样形成的码矢既匹配了各级子带的重要性,又利用到了带内和带间相关性,在相同的比特率下,其重构图像的信噪比ＰＳＮＲ比码矢仅由带内系数组成的传统带内ＶＱ高出１～２ｄＢ。     

基于小波高频的立体图像质量评价

根据小波变换的高频分量包含边缘及纹理等人眼比较关注的细节信息,提出了一种基于小波变换的高频重构的立体图像质量评价方法,包括左右视点质量评价和立体感评价两部分。通过模拟人类视觉系统处理原始和失真的左右视点图像,利用结构相似度算法得到左右视点质量评价值;用加权处理后的小波高频分量经过重构得到人眼关注的细节信息图,分别计算原始和失真的左右视点细节信息图的绝对差值图,利用结构相似度算法对两幅绝对差值图评价得到立体感质量评价值。将两种质量评价值进行加权融合得到最终的立体图像质量评价值。整体实验结果的Pearson线性相关系数在0.94以上,Spearman秩相关系数值在0.93以上,均方根误差值接近5.5,能较好地符合人眼视觉特性。     

基于阈值式小波变换的波前重构算法

 针对传统的波前重构器计算效率低、稳态误差大的问题,提出了阈值式波基多分辨力波前重构算法,采用4维波基作为标准正交基,将波前相位畸变投射到4维波基上,使伪逆矩阵变为稀疏矩阵,有效地减少了计算量,并采用阈值法去除波前重构矩阵算子中对精度影响较小的高分辨力波基系数,进一步增加了矩阵的稀疏程度,提高了运算效率,并与传统的最小二乘法、Zernike模式法和迭代法进行了计算量和均方根误差的比较,仿真结果表明该算法无论在计算速度和收敛精度上均优于其它算法。     

基于小波变换的蓝宝石荧光光纤温度计

采用激光加热小基座法生长出掺Cr3+的蓝宝石光纤荧光温度传感头，它具有结构紧凑，耐高温等特点，测温范围从室温到450℃。使用基于小波变换的数据处理方法，有效去除信号中的噪声，提高了信噪比。在对荧光测温机理和有关光纤技术进行分析的基础上，采用与调制荧光信号相关的双参考源相位锁定测量方案，可在无激励光干扰的情况下对荧光寿命进行实时测量。根据噪音和信号在小波变换下表现出的不同性质，提出以小波变换为基础的温度信号特征提取及消噪方法。与其它处理方法相比，小波变换方法可以克服傅里叶变换对突变信号不起作用的缺点，同时又比Gabor变换具有可变窗口的优点。该方法可以缩短测量时间，提高测量分辨率。     

Single pixel imaging based on semi-continuous wavelet transform

Single pixel imaging is a novel imaging technique, and it becomes a focus of research in recent years due to its advantages such as high lateral resolution and high robustness to noise. Imaging speed is one of the critical shortcomings, which limits the further development and applications of this technique. In this paper, we focus on the issues of imaging efficiency of a single pixel imaging system. We propose semi-continuous wavelet transform(SCWT) protocol and introduce the protocol into the single pixel imaging system. The proposed protocol is something between continuous wavelet transform and discrete wavelet transform, which allows the usage of those smooth(usually non-orthogonal, and they have advantages in representing smooth signals compressively, which can improve the imaging speed of single pixel imaging) wavelets and with limited numbers of measurements. The proposed imaging scheme is studied, and verified by simulations and experiments. Furthermore, a comparison between our proposed scheme and existing imaging schemes are given. According to the results, the proposed SCWT scheme is proved to be effective in reconstructing a image compressively.     

基于阈值式小波变换的波前重构算法

针对传统的波前重构器计算效率低、稳态误差大的问题,提出了阈值式波基多分辨力波前重构算法,采用4维波基作为标准正交基,将波前相位畸变投射到4维波基上,使伪逆矩阵变为稀疏矩阵,有效地减少了计算量,并采用阈值法去除波前重构矩阵算子中对精度影响较小的高分辨力波基系数,进一步增加了矩阵的稀疏程度,提高了运算效率,并与传统的最小二乘法、Zernike模式法和迭代法进行了计算量和均方根误差的比较,仿真结果表明该算法无论在计算速度和收敛精度上均优于其它算法。     

基于小波变换的激光主动成像图像去噪方法

针对激光主动成像图像的特点,提出了将小波变换和中值滤波相结合的图像去噪方法。在对小波分解后的水平、垂直和对角3个方向高频细节图像进行处理时,我们采用3种不同形状的模板进行均值滤波,为了保护图像的边缘和细节信息,采用边缘检测法来将高频中的边缘细节与噪声分开。实验结果表明:该方法在降低图像噪声的同时又较好地保留了图像的细节,去噪效果比较理想。     

基于光学子波变换的SDF匹配滤波器

提出了一种基于光学子波变换的综合判别函数匹配滤波器(WFSDF),将光学子波变换和综合判别函数相结合,只用一个简单的4f系统就能实现输入图像和SDF子波变换的相关运算。采用计算全息的方法制作复数匹配滤波器。计算机模拟仿真结果表明,与传统的SDF匹配滤波器相比,WFSDF匹配滤波器,锐化了相关峰,提高了识别率,同时简化了光路,能够实现多目标的畸不变识别。     

一种基于小波变换的红外偏振融合算法

针对红外偏振图像可以较好地抑制背景噪声,对目标边缘信息比较敏感的特点,提出一种基于小波变换的红外偏振融合算法,它主要用于红外辐射强度图像和偏振度图像融合,增加图像的信息量。首先采用小波变换对参与融合的每幅图像分别进行各尺度分解,得到各尺度小波系数,然后针对不同尺度小波系数,采用邻域平均梯度为判据进行融合,得到融合后的各尺度小波系数,最后通过小波逆变换进行图像重构,得到融合图像。融合前后的图像对比表明融合图像在保留辐射强度图像的清晰度的同时,突出了目标的边缘、轮廓信息。相对于辐射强度图像,融合图像的梯度均值提高了112%,相对于偏振度图像,融合图像的标准差提高了151%,信息熵提高了38%。     

基于小波变换和矢量量化的语音压缩编码方案

对于一种新的语音压缩编码方法——基于小波变换和矢量量化的语音压缩编码方案进行了开发和研究。该方法先对语音进行小波变换和小波包变换,然后使用矢量量化来压缩数据.我们还研究了使用摘编码方法进一步降低比特率的算法,实验结果表明对于采样频率为8kHz,每样本量化为8bit的64kbit/s语音信号压缩到6kbit/s~8kbit/s时,具有良好的语音质量.同时该算法还具有低延迟的优点,其算法延迟只有8ms。     

小波变换在变压器励磁涌流识别中的应用

为防止励磁涌流导致变压器的差动保护误动作,本文提出了一种以小波系数分布为判据的励磁涌流识别的新方法。该方法以小波变换中多分辨分析为理论依据,通过小波变换后对所得二尺度上的小波系数进行提取,计算其方差变化率来表示小波系数的变化情况,并设定合理的阀值,来对励磁涌流与故障电流进行区分。应用MATLAB工具箱搭建变压器励磁涌流与故障电流仿真模型,进行大量仿真,仿真试验结果表明,该方法能够快速有效的对励磁涌流与故障电流进行识别判断,克服了传统方法的不足,保证差动保护的正确动作,具有很高的应用前景。     

基于梯度和小波变换的水下距离选通图像去噪

水体的散射效应、激光光斑、成像器件的非理想化等因素使得图像出现大量无规律粒状噪声,它们增加了水下距离选通图像的背景噪声,模糊了目标轮廓,掩盖了目标细节,降低了图像的信噪比。针对上述问题本文提出了一种基于梯度和小波变换的去噪方法。首先对图像进行余弦小波变换,得到不同频率空间的图像集。低频空间引入新的图像梯度强化方法以提高图像的纹理信息量;对应非均匀性条带的LH或HL空间做曲面拟合处理以消除非均匀性条带的影响;在HH空间去噪过程中,低层空间做非局部均值处理以保留图像相似信息,高层空间做分数阶积分处理以保留图像细节信息。最后小波逆变换得到结果图像。从实验水槽中采集水下图像进行算法验证,将改进方法与已有算法比对分析。实验表明,本文所研究的水下去噪算法,能够平滑噪声且更大限度地保留图像细节纹理,在客观评价指标上提升了6%。     

提升小波加权自相关函数的基音检测算法*

随着计算机技术的发展,语音信号处理作为人机交互的重要渠道,其在复杂噪声环境下的特征值检测算法直接关系到计算机的运算效率。基音周期是语音特征值提取的重要参数之一。针对传统基音检测算法在噪声环境下检测精度低的问题,提出了一种基于自适应提升小波变换加权线性预测误差自相关函数的基音检测算法。该方法用多级提升小波近似系数加权求和的方法来弥补自相关函数随着时间延迟量的增加幅值衰减的缺陷;用线性预测误差自相关函数的方法来抑制共振峰的干扰,然后将两种方法结合来突出基音周期处的峰值。实验结果表明,与传统的自相关函数法和小波加权法相比,该方法能有效减弱共振峰的影响,突出基音周期处的峰值,提高基音周期检测精度,鲁棒性更好。     

Phase recovery from fringe patterns using the continuous wavelet transform

Interferometry is well established as an optical technique in which a measurand is encoded as the phase of a periodically varying intensity pattern. In view of the inherent accuracy of interferometry, many methods have been developed to retrieve the phase from images of the fringe pattern. Our focus in this paper is one such technique—the continuous wavelet transform (CWT). We begin by reviewing the CWT and the space–spatial–frequency localisation properties of wavelets. We show that a path which follows the maximum modulus of the CWT (the wavelet ridge) gives the instantaneous fringe frequency as a function of spatial displacement. The phase is automatically and trivially obtained, without discontinuities, by integration. Examples of practical wavelets are given and algorithms to isolate the wavelet ridge reviewed.     

基于小波变换的信号去噪在瑞利-泰勒不稳定性定标实验中的应用

 采用Daubechies小波分析,对神光Ⅱ装置上流体力学不稳定性实验中样品扰动幅度和X光强度之间定标关系的数据进行了处理,获得了比较理想的去噪效果,并由此得到了平面调制靶波长及材料线性吸收系数等细节信息。该定标关系对准确测量瑞利-泰勒不稳定性的增长至关重要。作为对比,利用Wiener滤波方法对数据进行了处理,结果显示在处理这类信号时,Daubechies小波滤波在去除噪声和保留信号细节特征方面明显优于Wiener滤波。     

基于离散平稳小波变换的红外图像去噪

提出了一种基于离散平稳小波变换的红外图像去噪方法。在预先不知道噪声方差的前提下,只利用红外图像的输入数据就可以确定所要求的渐近最优阈值。对红外图像进行离散平稳小波变换后,分别对各个分解层的高频子带利用所提出的方法进行迭代去噪,使各个高频子带分别收敛于其最大信噪比。实验结果表明,所提出的方法在有效的去除红外图像噪声的同时,又能较好的保持红外图像的细节部分信息。算法在性能指标和视觉质量上均优于基于离散正交小波变换的阈值去噪方法和传统的中值滤波法。