基于小波的多极化机载合成孔径雷达海面风向反演

为了实现从合成孔径雷达(SAR)图像本身提取高精度的海面风向信息, 提高SAR海面风场反演精度,研究了多极化机载SAR海面风向反演技术, 借助小波分析相对傅里叶分析和局部梯度更精细的时-频分析能力, 将二维连续小波变换与快速傅里叶变换(FFT)相结合,提出一种新的机载SAR海面风向反演方法. 为验证反演方法的有效性,通过海上同步飞行试验获取多极化机载SAR数据及同步调查船实测风向数据,用于反演试验的数据比对.采用本文提出的方法, 利用多种小波基对机载C波段SAR的同极化和交叉极化数据进行风向反演, 将反演结果与美国国家环境预报中心再分析资料以及调查船实测风向进行比对. 结果表明,本文提出的基于小波分析的海面风向反演方法适用于机载SAR探测数据, 反演精度优于二维FFT法和局部梯度方法;小波基的选择对反演结果影响较大, Mexican-Hat小波基是机载SAR海面风向反演的最优小波基, 且同极化与交叉极化机载SAR数据均可用于海面风向的反演.     

亚像素多重分形方法在图像处理中的应用

提出了一种用亚像素多重分形原理求取图像奇异性的新型算法,降低了单纯依靠整数像素位置灰度级梯度信息计算边缘测度所产生的误差。该算法结合CCD成像机理给出在亚像素位置的灰度级梯度分布规律,利用多重分形理论将实际图像分割成一系列具有不同奇异性指数的分形集合,对应着从边缘到纹理各层面的图像内容。模拟计算了投影小波中心点改变单位距离对边缘测度的影响程度,得出亚像素分割梯度的方法可以增加计算结果鲁棒性的结论。此方法用于标准图像的分割中,选用5×5亚像素数目提取的最奇异性集合与索贝尔(Sobel)算子(默认阈值为36.7920)提取的边缘的峰值信噪比为9.3981 dB。应用于复杂路面的裂纹提取中,其结果更符合人类的视觉观测。     

Empirical evidences of a common multifractal signature in economic, biological and physical systems

Recent developments in microcanonical multifractal formalism have lead to a sensible improvement in the numerical techniques for the determination of the multifractal characteristics of real signals. With the aid of these techniques, we have found empirical evidence of a common multifractal signature in six very different systems, ranging from stock market time series to sea surface temperature records. These systems are not only found to be multifractal, but their singularity spectra are coincident. We propose an explanation of this striking coincidence in terms of a cascade process and analyze its consequences.     

Multifractal properties of Chinese stock market in Shanghai

In this article, we apply three methods of multifractal analysis, partition function method, singular spectrum method and multifractal detrended fluctuation analysis method, to analyze the closing index fluctuations of Shanghai stock market during the past seven years. We have found that Shanghai stock market has weak multifractal features and there are long-range power-law correlations between index series. The shapes of singular spectrums do not change with time scales and their strengths weaken when the scales shorten. But when the orders of partition function increase, the strengths of multifractal increase, the singular spectrums become rougher and the general Hurst exponents decrease. These results provide solid and important values for further study on the dynamic mechanism of stock market price fluctuation.     

Oscillating singularities on cantor sets: A grand-canonical multifractal formalism

The singular behavior of functions is generally characterized by their Hölder exponent. However, we show that this exponent poorly characterizes oscillating singularities. We thus introduce a second exponent that accounts for the oscillations of a singular behavior and we give a characterization of this exponent using the wavelet transform. We then elaborate on a grand-canonical multifractal formalism that describes statistically the fluctuations of both the Hölder and the oscillation exponents. We prove that this formalism allows us to recover the generalized singularity spectrum of a large class of fractal functions involving oscillating singularities.     

基于小波leaders的海杂波时变奇异谱分布分析

海杂波的奇异谱分析不仅能从理论上揭示海洋表面的动力学机理,同时也是对海探测雷达的关键技术之一.本文提出基于小波leaders的海杂波时变奇异谱分析方法,将时间信息引入海杂波的奇异谱分析之中,从而实现动态的解析描述海杂波随时间变化的奇异谱特性.在理论上,通过信号自身加窗,将时间信息引入传统的奇异谱(或称多重分形谱),实现了对海杂波时变奇异谱分布分析;在算法上,充分利用了小波leaders技术对于多种奇异性的提取能力(包括chirp奇异性和cusp奇异性),通过对时变奇异性指数和时变尺度函数的Legendre变换,实现对海杂波时变奇异谱分布的计算;在应用部分,采用经典的多重分形模型——随机小波序列(RWC)以及三级海态条件下连续波多普勒体制雷达海杂波进行仿真分析,实验结果表明:1)基于小波leaders的奇异谱分布能跟踪海杂波的时变尺度特性,有效展示其时变奇异性谱分布;2)算法具有较好的负矩特性和统计收敛性.该方法能为复杂非线性系统及随机多重分形信号分析提供参考.     

Relationships of exponents in multifractal detrended fluctuation analysis and conventional multifractal analysis

Multifractal detrended fluctuation analysis (MF-DFA) is a relatively new method of multifractal analysis. It is extended from detrended fluctuation analysis (DFA), which was developed for detecting the long-range correlation and the fractal properties in stationary and non-stationary time series. Although MF-DFA has become a widely used method, some relationships among the exponents established in the original paper seem to be incorrect under the general situation. In this paper, we theoretically and experimentally demonstrate the invalidity of the expression τ(q)=qh(q)-1 stipulating the relationship between the multifractal exponent τ(q) and the generalized Hurst exponent h(q). As a replacement, a general relationship is established on the basis of the universal multifractal formalism for the stationary series as τ(q)=qh(q)-qH'-1, where H' is the nonconservation parameter in the universal multifractal formalism. The singular spectra, α and f(α), are also derived according to this new relationship.     

Singularity spectrum of fractal signals from wavelet analysis: Exact results

The multifractal formalism for singular measures is revisited using the wavelet transform. For Bernoulli invariant measures of some expanding Markov maps, the generalized fractal dimensions are proved to be transition points for the scaling exponents of some partition functions defined from the wavelet transform modulus maxima. The generalization of this formalism to fractal signals is established for the class of distribution functions of these singular invariant measures. It is demonstrated that the Hausdorff dimensionD(h) of the set of singularities of Hölder exponenth can be directly determined from the wavelet transform modulus maxima. The singularity spectrum so obtained is shown to be not disturbed by the presence, in the signal, of a superimposed polynomial behavior of ordern, provided one uses an analyzing wavelet that possesses at leastN>n vanishing moments. However, it is shown that aC behavior generally induces a phase transition in theD(h) singularity spectrum that somewhat masks the weakest singularities. This phase transition actually depends on the numberN of vanishing moments of the analyzing wavelet; its observation is emphasized as a reliable experimental test for the existence of nonsingular behavior in the considered signal. These theoretical results are illustrated with numerical examples. They are likely to be valid for a large class of fractal functions as suggested by recent applications to fractional Brownian motions and turbulent velocity signals.     

Mechanisms for the SAR Imaging of the Ocean

We perform a comparative analysis of two mechanisms for the formation of a synthetic aperture radar (SAR) image of the ocean, which are related to orbital velocities on the surface. It is shown that the mechanism of fluctuations of the effective density of scatterers, which is commonly accepted at present as the physical basis for the SAR diagnostics of roughness, actually works only in the case of a sufficiently flat swell. In the presence of wind roughness, the dominant role is played by another mechanism, namely, fluctuations of the number of surface elements whose images are randomly shifted and superimposed in the image plane due to orbital velocities. In the case of a developed wind roughness propagated in the azimuthal direction, the power contributions of two above-mentioned mechanisms to the SAR imaging of the ocean differ by about two orders of magnitude.     

Surface quasigeostrophic turbulence: The study of an active scalar

We study the statistical and geometrical properties of the potential temperature (PT) field in the surface quasigeostrophic (SQG) system of equations. In addition to extracting information in a global sense via tools such as the power spectrum, the g-beta spectrum, and the structure functions we explore the local nature of the PT field by means of the wavelet transform method. The primary indication is that an initially smooth PT field becomes rough (within specified scales), though in a qualitatively sparse fashion. Similarly, initially one-dimensional iso-PT contours (i.e., PT level sets) are seen to acquire a fractal nature. Moreover, the dimensions of the iso-PT contours satisfy existing analytical bounds. The expectation that the roughness will manifest itself in the singular nature of the gradient fields is confirmed via the multifractal nature of the dissipation field. Following earlier work on the subject, the singular and oscillatory nature of the gradient field is investigated by examining the scaling of a probability measure and a sign singular measure, respectively. A physically motivated derivation of the relations between the variety of scaling exponents is presented, the aim being to bring out some of the underlying assumptions which seem to have gone unnoticed in previous presentations. Apart from concentrating on specific properties of the SQG system, a broader theme of the paper is a comparison of the diagnostic inertial range properties of the SQG system with both the two- and three-dimensional Euler equations. (c) 2002 American Institute of Physics.     

Microcanonical scaling in small systems

A microcanonical finite-size scaling ansatz is discussed. It exploits the existence of a well-defined transition point for systems of finite size in the microcanonical ensemble. The best data collapse obtained for small systems yields values for the critical exponents in good agreement with other approaches. The exact location of the infinite system critical point is not needed when extracting critical exponents from the microcanonical finite-size scaling theory.     

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%。     

Multifractal Analysis of Complex Random Cascades

We achieve the multifractal analysis of a class of complex valued statistically self-similar continuous functions. For we use multifractal formalisms associated with pointwise oscillation exponents of all orders. Our study exhibits new phenomena in multifractal analysis of continuous functions. In particular, we find examples of statistically self-similar such functions obeying the multifractal formalism and for which the support of the singularity spectrum is the whole interval [0, ∞].     

Imagery of ocean waves by synthetic aperture radar

We consider the image structure of ocean waves produced by a synthetic aperture radar (SAR). The theory takes account of the spatial and temporal dependence of small scale capillary waves and large scale waves. Detailed discussions are given to the imaging process in which both amplitude modulation and velocity bunching contribute to the final images. Discussions are also presented on the effect of defocussing on the images of azimuth waves.     

A new approach for colored watermarking image into gray scale image using wavelet fusion

With the quick growth of technologies and great spread of the Internet, many challenges face data hiding. Nevertheless, significant data may be protected by burring it in an image as a watermark. This paper shows an efficient data hiding watermarking approach for color image by using singular value decomposition (SVD), multi-level discrete wavelet transform (DWT) and wavelet fusion. The main idea in this work is to separate the color image into its basic components (three channels); red, green, and blue. Then, fuse every channel with an image which is gray scale and integrate the three fused images into one gray scale fused image. Finally, the fused image is burred into a cover gray scale image to produce the watermarked image by using DWT and SVD. The proposed approach evaluation is done by using several images and different hacking on the transmitted image. The experimental results show that the marked images which are generated by the proposed approach are tolerant to versatile attacks such as Gaussian, blur, wrap, and cropping. Above all, the extracted watermark images are recognized even when the watermarked images suffered from attacks.     

Unconventional multifractal formalism and image analysis of natural fractals

The unconventional multifractal formalism is compared with the conventional one frequently used to characterize nonlinear phenomena and complex systems. The algorithm for the unconventional formalism has been implemented on a computer. Numerical artifacts of the method are discussed. Empirical criteria for distinguishing the monofractality/multifractality of the spectra affected by statistical fluctuations are presented. The multifractal image analysis of the Lichenberg figures has confirmed a self-similar arrangement of surface streamers belonging to the special case of electrostatic separation discharges propagating along a surface of polymeric dislectrics.     

基于无人机载的光电与SAR图像融合技术研究

为了提高无人机侦察识别能力,提出基于小波变换方法的无人机载光电与SAR的图像融合技术。经时间配准算法生成图像配准源,采用SIFT算法提取图像特征点,BBF算法计算生成匹配点集,依据匹配点集计算图像间透视变换模型完成图像配准,利用小波变换算法实现配准图像融合。经实验验证以及利用Matlab分析图像灰度直方图和计算信息量,结果表明:融合图像保留了光电图像95.7%的细节(熵),相比于光电图像平均梯度提高了1.52倍,增强了光电图像目标区对比度,降低了随机性噪点;融合图像相比于SAR图像信息量提高了1.44倍。     

基于双树复小波变换的非平稳时间序列去趋势波动分析方法

多重分形去趋势波动分析是研究非平稳时间序列非均匀性和奇异性的有效工具, 针对该方法中趋势项难以确定的问题, 提出一种基于双树复小波变换的方法, 实现了非平稳信号的多重分形自适应去趋势波动分析. 利用双树复小波变换提取信号的多尺度趋势和波动信息, 通过小波系数的希尔伯特变换确定每个时间尺度不重叠子区间的长度, 使多重分形分析具有信号自适应性及较高的计算效率. 以具有解析形式分形特征的倍增级联信号和分数布朗运动时间序列为例验证本文方法的有效性, 所得结果与解析解相吻合. 与传统的多项式去趋势多重分形方法相比, 本文方法根据信号自身特点自适应地确定信号的趋势和不重叠等长度子区间长度, 所得结果更加精确. 对倍增级联信号时间序列取不同的长度, 验证了算法的稳定性. 分别与基于极大重叠离散小波变换和离散小波变换多重分形方法进行比较, 表明本文方法具有更精确的结果和更快的运算速度.