基于自适应小波变换和矢量量化的图像压缩编码

运用小波变换进行图像压缩的算法其核心都是小波变换的多分辨率分析以及对不同尺度的小波系数的量化和编码 .本文提出了一种基于能量的自适应小波变换和矢量量化相结合的压缩算法 .即在一定的能量准则下 ,根据子图像的能量大小决定是否进行小波分解 ,然后给出恰当的小波系数量化 .在量化过程中 ,采用一种改进的LBG算法进行码书的训练 .实验表明 ,本算法广泛适用于不同特征的数字图像 ,在取得较高峰值信噪比的同时可以获得较高的重建图像质量 .     

基于小波变换的信号奇异性分析

本文研究得出了用小波变换进行奇异性检测时的小波基的一些选取原则和检测算法，并应用实例予以验证，从而证明了这些原则的有效性，为小波变换在奇异性检测中的实践运用奠定了一定的理论基础．     

基于HIS和小波变换相结合的图像融合方法

分析了HIS变换在图像融合中产生颜色失真的原因,提出了将HIS变换和小波变换相结合的方法,有效地解决了融合中颜色失真的问题,并根据融合评价体系对实验结果进行评价.结果显示,方法与传统的HIS方法相比取得了更好的融合效果.     

一种基于Eno-Haar小波变换二维遗传算法

A two-dimensional genetic algorithm of wavelet coefficient is presented by using the ENO wavelet transform and the decomposed characterization of the two-dimensional Haar wavelet.And simulated by the ENO interpolation the article shows the affectivity and the superiority of this algorithm.     

傅立叶变换与小波变换的比较教学

本文针对小波变换教学中小流变换概念理解困难的问题，提出了一种比较教学方法，通过分析小波变换与傅立叶变换之间的联系，并从四个方面进行对比，清楚地描述了小波变换的本质，从而对加深对小波变换的理解。     

基于小波变换的图像去噪方法的研究

小波变换能有效的去除高斯噪声,中值滤波能有效的去除脉冲噪声,两者结合可以更有效的去除高斯噪声和脉冲噪声的混合噪声.当医学图像去除混合噪声时,先进行中值滤波再进行小波去噪的方法优于先进行小波去噪后再进行中值滤波的方法,且去噪后图像视觉效果较好,而且图像均方误差(M SE)也较小.在图像去噪处理中这种方法具有实际应用价值.     

基于遗传模拟退火算法的矢量量化码书设计

首先介绍了遗传算法和模拟退火算法等全局优化算法,并针对遗传算法的早熟现象和容易陷入局部最优的缺点,将模拟退火算法引入到遗传算法中,提出了遗传模拟退火矢量量化码书设计(GSAKVQ)算法.此外,针对基于划分的染色体编码方式的特点,算法提出了新的有效的交叉算子和变异算子.同时,将算法从输入空间映射到特征空间,提出了相应的遗传模拟退火核矢量量化算法,改善了算法在某些数据集上的不足.最后,通过实验表明,GSAKVQ算法,在大部分的数据集上都能取得较好的结果,从而验证了算法在数据聚类问题上的有效性.     

周期函数和非平稳周期函数的小波变换

探讨了三角函数、周期函数以及一类非平稳周期函数小波变换的一些性质,发现周期函数的小波能谱的峰高和峰宽均正比于信号的周期.提出了一个新的只利用与信号周期有关的一个尺度小波变换系数的重构公式,它可准确地重构三角函数,对一般周期函数的重构结果优于其Fourier级数中的任何一项,对一类均值和振幅变化的非平稳周期函数的重构结果与信号非常吻合.     

正交小波变换的向量空间算法

本文揭示了一个事实，小波不仅可构成Ｌ２空间中的正交基，小波分解与重构滤波还可产生Ｎ维空间中的正交基．在本文提出修改的小波变换算法之下，Ｎ点信号的小波变换等价于Ｎ维空间中的正交变换．用该算法进行信号或图象压缩，无需对信号或图象进行周期延拓，可严格地在Ｎ维空间中进行．     

由一元连续小波变换得到的二元连续小波变换及重构公式

讨论了L2(R2)空间中连续小波变换,分别得到由一元变换函数构造二元变换函数的二元小波变换及重构公式,得到重构公式在L2(R2)中范数收敛意义下成立的条件.     

基于小波变换和人眼视觉系统特性的图像降噪方法

利用小波变换与人眼视觉系统（human visual system,HVS）的多通道特性相匹配的特点,提出一种基于人类视觉系统的图像降噪方法.该方法在P-M模型中引入小波变换与视觉敏感函数,并且结合视觉敏感函数的带通特性,提出一种新的扩散函数.实验结果表明,该方法得到的图像不论在客观评价（峰值信噪比）方面还是主观测评方面,都能达到较好的效果.     

Inverse radon transform with one-dimensional wavelet transform

1. IntroductionSince Radon obtained the inverse formula of Radon transform in 1917, different inversemethods such as Fourier inversion, convolution back-projection inversion etc. have beeninvestigated['l']. Wavelet as a useful tool is interested in the inversion of Radon transformin recent years['--']. The application of wavelet analysis to Radon transform was proposedin I4] and [5]. An inversion formula based on continuous wavelet transform was derivedin [6] and [7]. This formula was based…     

Fractal compression coding based on wavelet transform with diamond search

In this paper, a fractal image compression coding scheme based on wavelet transform with diamond search is proposed. The goal is to offer fast positioning. According to search pattern and search path of diamond search, the proposed scheme just needs to search in the domain blocks in the fixed place around the range blocks. Our proposed method has benefits in reducing the search time and enhancing the coding speed compared with other image compression techniques.     

Digital watermarking scheme for colour remote sensing image based on quaternion wavelet transform and tensor decomposition

Digital watermarking is important for protecting the intellectual property of remote sensing images. Unlike watermarking in ordinary colour images, in colour remote sensing images, watermarking has an important requirement: robustness. In this paper, a robust nonblind watermarking scheme for colour remote sensing images, which considers both frequency and statistical pattern features, is constructed based on the quaternion wavelet transform (QWT) and tensor decomposition. Using the QWT, not only the abundant phase information can be used to preserve detailed host image features to improve the imperceptibility of the watermark, but also the frequency coefficients of the host image can provide a stable position to embed the watermark. To further strengthen the robustness, the global statistical feature structure acquired through the tensor Tucker decomposition is employed to distribute the watermark's energy among different colour bands. Because both the QWT frequency coefficients and the tensor decomposition global statistical feature structure are highly stable against external distortion, their integration yields the proposed scheme, which is robust to many image manipulations. A simulation experiment shows that our method can balance the trade‐off between imperceptibility and robustness and that it is more robust than the traditional QWT and discrete wavelet transform (DWT) methods under many different types of image manipulations.     

The quadratic-phase Fourier wavelet transform

In this paper, we define the quadratic-phase Fourier wavelet transform (QPFWT) and discuss its basic properties including convolution for QPFWT. Further, inversion formula and the Parseval relation of QPFWT are also discussed. Continuity of QPFWT on some function spaces are studied. Moreover, some applications of quadratic-phase Fourier transform (QPFT) to solve the boundary value problems of generalized partial differential equations.     

Mexican hat wavelet transform of distributions

Theory of Weierstrass transform is exploited to derive many interesting new properties of the Mexican hat wavelet transform. A real inversion formula in the differential operator form for the Mexican hat wavelet transform is established. Mexican hat wavelet transform of distributions is defined and its properties are studied. An approximation property of the distributional wavelet transform is investigated which is supported by a nice example.     

Cauchy wavelet transform of ultra-distributions in tube domains

In this paper, Cauchy wavelet transform of ultra-distributions in tube domains is defined and its various properties are studied using the theory of Cauchy integrals and Poisson integrals of ultra-distributions.     

一种利用多通道小波变换去噪的算法

通过对多通道小波和小波变换以及奇异信号的小波变换特性的讨论和分析,提出了一种利用M道小波变换去噪的算法,并利用此算法对加噪信号进行了模拟实验,实验结果表明,该算法简便,易于编程实现且去噪效果理想。     

Spherical wavelet transform and its discretization

A continuous version of spherical multiresolution is described, starting from continuous wavelet transform on the sphere. Scale discretization enables us to construct spherical counterparts to wavelet packets and scale discrete wavelets. The essential tool is the theory of singular integrals on the sphere. It is shown that singular integral operators forming a semigroup of contraction operators of class (C ₀) (like Abel-Poisson or Gauß-Weierstraß operators) lead in a canonical way to (pyramidal) algorithms.Supported by the Graduiertenkolleg Technomathematik, Kaiserslautern.