小波图象处理软件

小波变换的一些源程序-wavelet transform some source

滤波器系数重构运用该算法可以对图象进行去噪处理-reconstruction filter coefficients using this algorithm can be right image denoising

可以用CDF53小波对灰度图像实现正反变换-CDF53 wavelet can be used to achieve positive and negative gray image transformation

本实例介绍晓波算法在VC++中的具体实现，这个为一维效波变换效果。-Xiaobo examples of this algorithm in VC is a concrete realization of the effect of one-dimensional wavelet transform effect.

小波变换具有良好的时―频局部性，是分析奇异信号的重要方法定点DSP在工程中的厘用士分背通，具实现小波变换可以满足工程是实时性的要求文中简要介绍了小波变换理论及算法，并结合TI公司的16位定点说明算法的实现。 -Wavelet transform has a good time- frequency localization, is to analyze the singular signal an important means of fixed-point DSP in engineering per cent pass with disabilities at the back with the realization of wavelet transform to meet the project is a real-time requirements of the article a brief introduction of wavelet transform theory and algorithm, combined with TI

Wavelets for computer graphics A primer

小波变换源程序,EZW算法-source wavelet transform, EZW Algorithm

3次非标准小波分解和重构， 使用两种小波：Haar小波和db9小波 设计3级小波分解和重构图像的程序 用你自己的照片作对象，显示其中任一种小波图像分解和重构过程 使用Haar小波时，计算阈值分别为0，5，10和20的情况下，用PNG格式存储重构的图像，并将计算结果填入“图像测试表” 使用db9小波时，计算阈值分别为0，5，10和20的情况下，用PNG格式存储重构的图像，并将计算结果填入“图像测试表” -3rd standard wavelet decomposition and reconstruction, the use of two wavelet : Haar wavelet and wavelet design Terminal 3 wavelet decomposition and reconstruction process images using your own pictures for targets, which shows the image of a wavelet decomposition and reconstruction process using wavelet Haar, the threshold values were calculated for 0, 5,10 and 20 of the cases, the storage format used PNG Image Reconstruction and results Enter "Image table test" Wavelet use Terminal, the threshold values were calculated for 0,5,10 and 20 of the cases, the storage format used PNG Image Reconstruction and calculation results Enter "Image test Table"

精彩的小波变换，不下是你的错。快来吧快下载吧-Wonderful wavelet transform, at least it is your fault. Come fast to download it now

利用小波变换对信号进行分析处理,现代信号处理,胡广书编-using wavelet analysis of signal processing, modern signal processing, Mr Kwong Textbook