W53和D97小波的小波提升原理，很易懂！英文。

matlab中都是对灰度图像进行小波变换，本程序是对彩色图像进行小波变换-matlab in gray-scale images are wavelet transform, this process is a wavelet transform for color image

对bmp图像的小波变换，包括其应用，如图像的滤波-bmp image of the wavelet transform, including its applications, such as image filtering

简单的哈尔小波变换。程序实现的功能如下：输入图像，界面中可以看到图像经变换所产生的变化-Simple Haar wavelet transform. Realize the function of the procedure are as follows: the input image, the interface can be seen in images generated by the transformation changes

本书的目的主要是向读者展示傅里叶分析和小波的许多基础知识以及在信号分析方面的应用。全书分为8章和2个附录，前言部分是学习第1章至第7章的准备知识，即内积空间；第1章讲解傅里叶系列的基础知识；第2章讲解傅里叶变换；第3章介绍离散傅里叶变换以及快速傅里叶变换；第4章至第7章讨论小波，重点在于正交小波的构建；附录部分则介绍稍微复杂的一些技术主题以及演示概念或产生图形的MATLAB代码。许多关于小波的文章和参考书籍均要求读者具有复杂的数学背景知识，本书则只要求学生具有较好的微积分以及线性代数知识，通俗易懂，是数学、计算机、电子、通信、地质、医学、机械等专业高年级本科生及研究生的基础教科书，也可作为相关技术人员的参考书。-The main purpose of this book is to show readers Fourier and wavelet analysis of many of the basic knowledge as well as in signal analysis applications. The topics are divided into eight chapters and two appendices, is to learn from the preamble of Chapter 1 to Chapter 7 of the preparation of knowledge, that is, inner product space Chapter 1 on the basis of Fourier series of knowledge Chapter 2 on Fourier Transform Chapter 3 introduced the Discrete Fourier Transform and Fast Fourier Transform Chapter 4 to Chapter 7 to discuss wavelet, with emphasis on construction of orthogonal wavelet appendix describes slightly complex themes, as well as a number of technical concepts or pr

基于小波变换模极大的多尺度图像边缘检测matlab源代码-based on wavelet transform modulus maxima of multiscale edge detection Matlab source code

这是关于小波变换的VC源码,test_images 目录下存放是各章程序所需的标准图像 其他目录存放的则是相应章节的程序源代码。 各章节源代码的说明见各个章节的子目录。-This is a wavelet transform on the VC source, test_images storage directory is required for the various chapters of the standards process images stored in other directories is the corresponding source code sections. Various sections of the source code is described in various sections of the subdirectories.

由于成像方式及波谱接收段的不同.合成孔径雷达SAR(synthetic aperture radar)与可见光图像所反映的信息有很大差异，图像之间相关性弱，且互补性明显。因此在图像融合时，应该根据其互补性信息特征各取所长。在研究了一些现有融合方法的基础上，提出了一种基于互补信息特征的SAR与可见光图像融合方法。首先通过基于像素邻域的能量统计特性融合SAR与可见光图像，将SAR图像中的重要目标信息加入到可见光图像中，然后再利用小波变换进行二次融今，充分加入原始图像的边缘细节信息。实验结果表明，该融合方法有效。-err

二维小波分析对图像处理的应用-wavelet analysis of 2D image processing applications

vc写的实现小波处理，滤波，复原，融合等源程序-vc wrote realize wavelet processing, filtering, restoration, integration, such as source

这是基于小波变换的零树编码程序-This is based on the wavelet transform coding procedures Zerotree