Multi-scale wavelet analysis of TOPEX/Poseidon altimeter significant wave height in eastern China seas

The multi-scale characteristics of wave significant height （Hs） in eastern China seas were revealed by multi-scale wavelet analysis. In order to understand the relation between wave and wind, the TOPEX/Poseidon measurements of Hs and wind speed were analyzed. The result showed that Hs and wind speed change in multi-scale at one-, two-month, half-, one- and two-year cycles. But in a larger time scale, the variations in Hs and wind speed are different. Hs has a five-year cycle similar to the cycle of ENSO variation, while the wind speed has no such cycle. In the time domain, the correlation between Hs and ENSO is unclear.

Improved significance testing of wavelet power spectrum near data boundaries as applied to polar research

When one applies the wavelet transform to analyze finite-length time series, discontinuities at the data boundaries will distort its wavelet power spectrum in some regions which are defined as a wavelength-dependent cone of influence （COI）. In the COI, significance tests are unreliable. At the same time, as many time series are short and noisy, the COI is a serious limitation in wavelet analysis of time series. In this paper, we will give a method to reduce boundary effects and discover significant frequencies in the COI. After that, we will apply our method to analyze Greenland winter temperature and Baltic sea ice. The new method makes use of line removal and odd extension of the time series. This causes the derivative of the series to be continuous （unlike the case for other padding methods）. This will give the most reasonable padding methodology if the time series being analyzed has red noise characteristics.

A method to compress vibration signals using wavelet packet transformation combined with sub-band vector quantization

A novel compression method for mechanical vibrating signals,binding with sub-band vector quantization(SVQ) by wavelet packet transformation(WPT) and discrete cosine transformation(DCT) is proposed.Firstly,the vibrating signal is decomposed into sub-bands by WPT.Then DCT and adaptive bit allocation are done per sub-band and SVQ is performed in each sub-band.It is noted that,after DCT,we only need to code the first components whose numbers are determined by the bits allocated to that sub-band.Through an actual signal,our algorithm is proven to improve the signal-to-noise ratio(SNR) of the reconstructed signal effectively,especially in the situation of lowrate transmission.

Video Compression USING a New Active Mesh Based Motion Compensation Algorithm in Wavelet Sub-Bands

In this paper, a new mesh based algorithm is applied for motion estimation and compensation in the wavelet domain. The first major contribution of this work is the introduction of a new active mesh based method for motion estimation and compensation. The proposed algorithm is based on the mesh energy minimization with novel sets of energy functions. The proposed energy functions have appropriate features, which improve the accuracy of motion estimation and compensation algorithm. We employ the proposed motion estimation algorithm in two different manners for video compression. In the first approach, the proposed algorithm is employed for motion estimation of consecutive frames. In the second approach, the algorithm is applied for motion estimation and compensation in the wavelet sub-bands. The experimental results reveal that the incorporation of active mesh based motion-compensated temporal filtering into wavelet sub-bands significantly improves the distortion performance rate of the video compression. We also use a new wavelet coder for the coding of the 3D volume of coefficients based on the retained energy criteria. This coder gives the maximum retained energy in all sub-bands. The proposed algorithm was tested with some video sequences and the results showed that the use of the proposed active mesh method for motion compensation and its implementation in sub-bands yields significant improvement in PSNR performance.

Improving the understanding of the influencing factors on sea level based on wavelet coherence and partial wavelet coherence

Relationship between sea level change and a single climate indicator has been widely discussed.However,few studies focused on the relationship between monthly mean sea level(MMSL)and several key impact factors,including CO_(2) concentration,sea ice area,and sunspots,on various time scales.In addition,research on the independent relationship between climate factors and sea level on various time scales is lacking,especially when the dependence of climate factors on Nino 3.4 is excluded.Based on this,we use wavelet coherence(WC)and partial wavelet coherence(PWC)to establish a relationship between MMSL and its influencing factors.The WC results show that the influence of climate indices on MMSL has strong regional characteristics.The significant correlation between Southern Hemisphere sea ice area and MMSL is opposite to that between Northern Hemisphere sea ice area and MMSL.The PWC results show that after removing the influence of Nino 3.4,the significant coherent regions of the Pacific Decadal Oscillation(PDO),Dipole Mode Index(DMI),Atlantic Multidecadal Oscillation(AMO),and Southern Oscillation Index(SOI)decrease to varying degrees on different time scales in different regions,demonstrating the influence of Nino 3.4.Our work emphasizes the interrelationship and independent relationship between MMSL and its influencing factors on various time scales and the use of PWC and WC to describe this relationship.The study has an important reference significance for selecting the best predictors of sea level change or climate systems.

京津冀地区近50 a降水时空变化分析

为了明确京津冀地区近年来降水时空变化特征,使用线性回归、空间插值以及M-K显著性检验、相关性分析、小波分析等方法,结合地区DEM数据,对近50 a降水逐日、逐月数据进行处理分析。结果显示,京津冀地区年降水量呈不显著增加趋势,且存在平均周期约20 a的周期性变化;年降水的不稳定性在增强,除春季外,其余季节降水的不稳定性均在增强;夏季降水与年降水具有最强的相关性;年降水量呈现自东南沿海向西北内陆递减规律,春季、秋季、冬季降水呈现两侧多、中间少的特征,夏季降水与年降水分布特征一致;绝大部分地区年降水量呈增加趋势,增幅的空间分布与年降水量的空间分布趋势相反,夏季降水与年降水在空间上仍然具有最高的一致性。

Sub-band ICA with selection criterion for BBS of dependent mages

Because of the correlation of images,the efficiency of the standard ICA is not satisfied in the blind source separation (BSS) of image.Therefore,a new method of sub-band ICA with selection criterion is proposed for this problem.Firstly,the sub-bands of the new method are made up of the wavelet packets (WP) coefficients.Secondly,the selection criterion of the new method is a combination of the mutual information (MI),kurtosis and sparsity.One sub-band or a sub-bands group obtained from the new method are more suitable as the inputs parameters of the algorithm of ICA than mixed images.The new method has been applied into the BSS of partially dependent images and highly dependent images successfully.According to the separation experiments,it is shown that the separation efficacy of the new method is more accurate and robust.

Statistical analysis of Epileptic activities based on Histogram and Wavelet-Spectral entropy

Epilepsy is a chronic neurological disorder which is identified by successive unexpected seizures. Electroencephalogram (EEG) is the electrical signal of brain which contains valuable information about its normal or epileptic activity. In this work EEG and its frequency sub-bands have been analysed to detect epileptic seizures. A discrete wavelet transform (DWT) has been applied to decompose the EEG into its sub-bands. Applying histogram and Spectral entropy approaches to the EEG sub-bands, normal and abnormal states of brain can be distinguished with more than 99% probability.

Information Hiding Method Based on Block DWT Sub-Band Feature Encoding

For realizing of long text information hiding and covert communication, a binary watermark sequence was obtained firstly from a text file and encoded by a redundant encoding method. Then, two neighboring blocks were selected at each time from the Hilbert scanning sequence of carrier image blocks, and transformed by 1-level discrete wavelet transformation (DWT). And then the double block based JNDs (just noticeable difference) were calculated with a visual model. According to the different codes of each two watermark bits, the average values of two corresponding detail sub-bands were modified by using one of JNDs to hide information into carrier image. The experimental results show that the hidden information is invisible to human eyes, and the algorithm is robust to some common image processing operations. The conclusion is that the algorithm is effective and practical.

Face Recognition Using LDA with Wavelet Transform Approach

Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over the standard Principal Component Analysis （PCA） method of face recognition by introducing the concept of classes and distance between classes. This paper provides an overview of PCA, the various variants of LDA and their basic drawbacks. The paper also has proposed a development over classical LDA, i.e., LDA using wavelets transform approach that enhances performance as regards accuracy and time complexity. Experiments on ORL face database clearly demonstrate this and the graphical comparison of the algorithms clearly showcases the improved recognition rate in case of the proposed algorithm.

太湖流域降水量变化及其与组合大气环流的关系

【目的】探明太湖流域降水量变化及与大气环流的多尺度效应。【方法】采用Mann Kendall(MK)、Modified Mann Kendall(MMK)趋势检验法以及小波相干分析(Wavelet Coherence,WTC)、多小波相干分析(Multiple Wavelet Coherence,MWC),对太湖流域1960—2020年30个气象站的降水量变化及其与单个和组合大气环流因子的多尺度振荡关系进行分析。【结果】①MMK及MK的趋势值在年尺度降水量及季节尺度降水量的空间分布相似,但显著性存在差异。年降水量上升趋势最大,而冬季降水量上升趋势最小。MMK可以检测出MK无法检测出的显著性,尤其是对于春季降水量。②WTC分析结果表明,太湖流域降水量与大气环流因子具有复杂的非线性关系,不同时域具有明显差异。③从单要素来看,EASM是太湖流域最具影响力的遥相关;在多要素组合中,Prep-AO-PDO-ENSO-EASM-DMI组合对流域降水量影响最大。【结论】单独的主导遥相关并不能很好地解释降水量与大气环流的关系,具有最高显著功率数百分比(POSP)的大气环流组合可作为解释降水量变化的最佳组合。

一种新的基于量子小波变换的图像水印算法

图像水印是一种将特定信息嵌入载体图像中的技术,用于版权保护。研究了一种新的基于量子小波变换的图像水印方案,包括置乱过程、嵌入过程和提取过程。其中采用改进的量子Arnold置乱方法对二值图像进行置乱,置乱后的水印图像应用于载体图像的最低有效分块量子位,对载体灰度图像采用量子Haar小波变换和量子最低有效位(LSB)分块技术,将置乱后的水印图像嵌入量子小波系数。首先从嵌入图像中提取置乱水印图像,然后利用改进的量子Arnold逆置乱方法进行逆置乱,获取原始水印图像。仿真技术验证了基于该量子图像水印方法水印的不可见性和高鲁棒性。通过峰值信噪比(PSNR)检验证明了该方案的不可见性。通过误码率(BER)检验和归一化相关系数(NC)检验了该方案的高鲁棒性。仿真结果表明,该水印方案不仅具有可接受的视觉质量,而且对不同类型的攻击具有良好的抵抗能力。

Morlet小波显著性检验和精度分析在地磁场和地震活动性周期分析中的应用

首先通过对加入随机噪声的合成信号进行Morlet小波变换并进行显著性检验,分析所得信号的周期成分的显著性和非显著性,然后研究信号周期长短、信号观测时间段长短与精度之间的关系.在此基础上,以活动周期比较稳定的太阳黑子活动作为实例分析,结果显示本文的精度分析和显著性检验方法对于周期谱的精度和显著性研究是可行的.最后将该方法应用于全球地震活动周期谱的分析,求出全球地震活动周期谱及其显著性与精度.研究结果表明,在利用Morlet小波分析地磁场和地震活动性周期时引入显著性检验,并结合本文给出的精度,可以从数据中提取出周期谱及其显著性和精度.

基于小波变换的多光谱图像压缩方法

在分析多光谱图像小波变换后系数特点的基础上 ,提出了一种共享有效图的小波变换压缩方法(SSMWT)。该方法将小波变换压缩技术中的零树编码推广到多光谱图像压缩中 ,利用多光谱图像的结构相关性 ,对多幅小波图像只需构造一幅有效图 ,同时去除空间冗余和谱间结构冗余 ,并与K L变换相结合 ,进一步去除谱间统计冗余 ,实验表明了该方法的有效性。

小波功率谱Monte Carlo显著性检验的一个简易方案

对一个气象量时间序列p={P(t),t=1,n},通过相空间中的几何分析直观地阐明了Morlet小波功率谱W(t,k)的计算原理,给出了一个对W(t,k)作Monte Carlo显著性检验的方案。由于该方案中随机序列的产生与分析序列p的理论分布无关,实施简单易行。对6月100hPa南亚高压强度指数序列的小波功率谱显著性检验表明,该方案能充分揭示p中年际、年代际振荡随时间的变化,因而具有实际应用价值。

油气藏自然电位小波多尺度分解及其地球物理意义

油气藏自然电位是不同深度的油气层在地表所产生的自然电位的综合效应,可以应用小波多尺度分解方法将自然电位分解成小波1～n阶细节和n阶小波逼近.1阶小波细节反映近地表干扰,2～n阶小波细节反映了中间层油气藏所产生的异常,n阶小波逼近反映背景异常.分解后小波细节异常反映的储集层场源深度可以按经验公式估算.应用该方法对松辽盆地西部齐家北地区自然电位异常进行分解的结果显示,分解后的小波细节与已知油气分布有对应关系,可用小波分解方法来研究油层分布状况.

基于连续小波变换的大地电磁信号谱估计方法

在基于连续小波变换的大地电磁信号谱估计方法中 ,通过引入整体平均、小波系数收缩和显著性检验等统计技术 ,以提高谱估计的精度 .文中同时讨论了连续小波变换中各种参数的选取问题 ,给出了Morlet小波函数中尺度与傅里叶频率之间转换的经验公式 ,并给出了谱估计的具体算法 .结果表明 ,本文方法可有效压制较强的白噪声和局部相关噪声 .与FFT谱估计方法相比 ,该方法大大降低了对信号记录长度的要求 ,因而对大地电磁信号的处理有实际意义 .

一种改进的小波系数差异量化水印算法

针对Lin等提出的"基于小波系数差异化量化"(SDQ)的水印方法存在的问题,提出了一种改进的小波系数差异量化水印算法。算法在密钥的控制下,伪随机地选择中频子带中的两块共8个系数组成一组,嵌入1bit水印信息,显著提高了SDQ算法的安全性。算法改进了SDQ的差异量化方式,在保持图像原有的重要系数大小关系的基础上,通过对最大系数进行小幅度的量化来加强差异,进而提高鲁棒性,并通过差异信息和水印信息生成密钥来提取水印。实验结果表明,该算法能有效抵抗各种攻击,并且图像峰值信噪比可以保持在55dB左右。

基于局部显著边缘特征的快速图像配准算法

针对尺度不变的特征变换(SIFT)算法提取的特征点数目多、匹配耗时长、匹配精度不高等问题,提出了一种基于局部显著边缘特征的快速图像配准算法。该算法利用SIFT算法提取待选特征点,同时用小波边缘检测提取图像边缘,建立特征点周围邻域的边缘特征,筛选出具有显著边缘特征的特征点,结合Shape-context算子和边缘特征形成特征描述向量,采用欧氏距离作为匹配度量函数对筛选出的特征点进行初步匹配,然后用随机一致性检验(RANSAC)算法消除误匹配点对。实验结果表明,该算法有效控制了特征点的数量,提高了特征点的质量,缩小了特征搜索空间,提高了特征匹配的效率。

基于金字塔格型矢量量化(PLVQ)的多尺度图像编码

近年来 ,格矢量量化 ( LVQ)由于本身的特点和性质引起了人们的广泛兴趣 .由于小波图像系数的分布特点 ,本文选用金字塔格型矢量量化 ( PLVQ) .为了使 PLVQ更有效 ,作者提出了一种与图像本身无关的熵编码方法去消除 VQ输出冗余 .特别是 ,给出了由格点输出索引和由索引输出格点的快速算法 ,而且 ,在矢量量化中引入了重要图的概念 ,可以有效确定非零矢量的位置 .此外 ,还根据异步传输模式 ( ATM)的特点 ,选择了传输的优先级 .