小波分解在图像处理 Wavelets

This is a wavelet program.

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)

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)

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)

图象增强小波变换将一幅图象分解为大小、位置与方向都不同的分量。在做逆变换之前能改变小波变换域中某些系数的大小，，这样就能够洋选择的放大所感兴趣的分量而减小不需要的分量。给定一个图象信号，用二维小波分析析对图象进行增强处理。 (Image enhancement wavelet transform decomposition size, location and direction of the different components of an image. Wavelet transform domain, some the size of the coefficient can change before doing the inverse transformation, so can the component of interest to the amplification of the ocean choose to reduce the unwanted weight. Given an image signal, the analysis of two-dimensional wavelet analysis of image enhancement processing.)

小波包分解与重构使用，最佳树使用方法。小波分析理论与MATLAB实现实例。很好的程序，希望对大家有用。(Wavelet packet decomposition and reconstruction using the best tree to use. MATLAB implementation of wavelet analysis theory and examples. Very good program, I hope all of us. )

小波分解在图像处理和电能质量分析中应用广泛，本文应用小波分解的方法将高频的暂态信号提取出来，获取暂态信号的特征量，就能够有效地计算暂态信号。(Wavelet decomposition in image processing and power quality analysis is widely used, this application of wavelet decomposition method to extract high-frequency transient signals, to obtain the amount of transient characteristics of the signal, we can effectively calculate the transient signal.)

小波变换模极大值重建信号的matlab源程序，来源于胡广书的《现代信号处理教程》附属光盘(Wavelet transform modulus maxima reconstruction signal matlab source code, derived from HU-book " modern signal processing tutorial subsidiary Disc)

基于gabor小波变换的论文，对做人脸识别很有用(Gabor wavelet transform-based papers, do face recognition is useful)

对于PCA ，LDA，BIC，EBGM都有很详细的代码。但是需要在LINUX下配置运行。不过代码较有参考价值。(For PCA, LDA, BIC, EBGM have a very detailed code. But the need to configure to run under LINUX. However, a more useful code.)