yuanma

说明：  傅立叶功率谱法求纹理特征 可解压缩后直接执行(Fourier power spectrum method for texture features can be extracted directly after implementation)

通过设计Visual C程序源码对简单易懂的一维信号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波与Haar小波变换，从而的到小波分解系数；再通过改变分解的到的各层高频系数数进行信号的小波重构达到消噪噪的目的。在这一程序源码实现的过程中能直观地理解信号小波分解重构的过程与在信号消噪中的重要作用，和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。 可直接 (Design Visual C program source code on a simple one-dimensional signal with a Gaussian white noise Daubechies wavelet, Morlet wavelet and Haar wavelet transform, and thus to the wavelet coefficients and then change the decomposition to each storey wavelet reconstruction frequency coefficient of the number of signal to noise canceling noise. In the process of realization of this program source code can be intuitively understood the signal wavelet decomposition and reconstruction process and an important role in signal denoising, and the selection coefficient in the high frequency coefficients of the layers of the weight of processing noise cancellation signal impact. Can be directly)

数字信号处理C语言程序集。里面包含全部的数字信号处理中各种算法的C程序设计。(Digital Signal Processing C-assemblies. Which contains all of the digital signal processing algorithms in a variety of C programming.)

基于小波变换的图片重建 有完整代码 工程 以及说明 涉及到图片的切割(image reconstruction based on wavelet translate )

数字信号处理的c++库，很好的资源，作者很牛，包括数值计算与常用的信号处理分析,例如FFT、小波变换、功率谱估计等(Digital Signal Processing c++ library, a great resource,including numerical analysis and common signal processing，such as FFT, wavelet transform, power spectrum estimation)

This is a wavelet program.

基于论文<<Blur Detection for digital images using wavelet transform>>,使用Haar小波变换实现图像模糊度检测。(Based on paper <Blur Detection for digital images using wavelet transform> > , Using the Haar wavelet transform of image blur detection.)

说明：  基于vc++6.0 的图像对比度拉伸操作(vc 6.0 on the image contrast stretching operation)

实现离散余弦(TCD)变换(achieve discrete cosine (TCD) Transform)

基于DB4 的小波变换，实现了小波的分解与重构，可根据实际需要修改阈值的选取方法(Based DB4 wavelet transform to achieve wavelet decomposition and reconstruction, according to the actual need to modify the threshold selection method)