基于小波变换的图像压缩方法。应用SOPM改善。

此程序实现图象傅立叶变换、离散傅立叶变换和小波变换、可以自己设定小波变换的参数-this procedure image Fourier transform, discrete Fourier transform and wavelet transform, can set their own parameters of wavelet transform

小波分解与合成，嵌入式编码与解码程序，用于语音和图像压缩-Wavelet decomposition and synthesis, embedded encoding and decoding procedures for voice and image compression

基于图像抽取和小波变换的压缩方法，很值得参考-Extraction and image-based wavelet compression method, it is worth considering

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

一维信号离散小波分解与重构的VC程序，很经典的一个-One-dimensional discrete wavelet signal decomposition and reconstruction of the VC process, it is the classic one

小波去噪的C++程序，可用与想了解去噪原理与小波变换实现的初学者-Wavelet Denoising C++ Procedures that can be used and would like to know the theory and wavelet transform denoising realize beginner

用小波进行地震信号低切处理的例子-seismic wavelet signal processing low-cut examples

给予小波变换的图像处理，能够形成图像的分割与拼接-Given wavelet transform image processing, image segmentation can be formed with the splicing

关于小波变换的源程序-on wavelet transform source

一个非常有用的基于小波的图象压缩软件-a very useful wavelet-based image compression software