gabor2

利用Harr将图像进行3层小波变换，并进行重建。里面包含测试图片及变换后系数重新排列后的结构图。(Harr is used to transform the image into three-layer wavelet transform and reconstruct it. It contains the test picture and the structure chart of the coefficient rearrangement after transformation.)

小波包的程序源代码,对于小波包的理解很有用，非常适合初学者！(Wavelet Packet program source code, useful for the understanding of wavelet packet, very suitable for beginners!)

wavelet transform s code with details

本文通过比较第一代和第二代小波算法特点,引入二代小波提升结构的概念,提出了一种基于二代小波提升结构的快速图像边缘检测算法 对三次B样条小波基实现提升格式,通过计算大尺度下分解子图的模值和幅角来确定边缘 经过实验比较,能比经典的边缘检测算法得出更精确的边缘图像,同时通过与基于第一代小波算法的边缘检测比较,基于二代小波提升格式的边缘检测算法计算更快速,更高效。(In this paper, by comparing first-and second-generation wavelet algorithm features, the introduction of second generation wavelet to enhance the concept of structure, a second generation wavelet-based structure to enhance the rapid image edge detection algorithm on the three B-spline wavelet lifting scheme to achieve through Calculation of large-scale mold subgraph decomposition value and increase the edge angle to determine the experimental comparison, than the classical edge detection algorithm to draw a more accurate edge image, at the same time with the first generation of wavelet-based edge detection algorithm comparison, based on the Second generation wavelet lifting scheme edge detection algorithm is faster and more efficient.)

说明：  关于小波变换的ppt，有用的可以下载看看(Ppt on Wavelet Transform)

此函数基于二进小波的分解、重构的图像去噪(This function is based on the dyadic wavelet decomposition, reconstruction of the image denoising)

在理解了离散小波变换的基本原理和算法的基础上，通过设计VC程序对简单的一维信 号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波和Haar小波变换，从而得到小波分解系数；再通过改变分解得到的各层高频系数进行信号的小波重构达到消噪的目的。在这一程序实现的过程中能直观地理解信号小波分解重构的过程和在信号消噪中的重要作用，以及在对各层高频系数进行权重处理时系数的选取对信号消噪效果的影响。(In understanding the basis of discrete wavelet transform basic principles and algorithms, through the design VC program Daubechies wavelet, Morlet wavelet and Haar wavelet transform after a simple one-dimensional signal plus a Gaussian white noise, resulting wavelet coefficients wavelet reconstruction signal again by changing the layers to achieve high-frequency coefficients decomposed noise cancellation purposes. Can intuitively understand wavelet decomposition and reconstruction process and an important role in signal de-noising in the process of implementation of this program, and in the high-frequency coefficients when the weight of the layers selected for signal processing coefficients denoising affected.)

我实现的离散小波变换，可直接运行，采用三级变换(Discrete wavelet thransform)

高斯滤波.这段代码主要用于以为信号的高斯滤波。(Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter)

此程序用DWT(离散小波变换)实现二维小波变换(discrete wavelet transform )