WPandEMD

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)

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)

使用四元数小波变换图像流估计。是对“Coherent Multiscale Image Processing using Dual-Tree Quaternion Wavelets”的实现。代码很详细。(Use quaternion wavelet transform image flow estimation. Is the " Coherent Multiscale Image Processing using Dual-Tree Quaternion Wavelets" implementation. Code is very detailed.)

美国著名Rice大学的小波变换工具箱，非常实用，实现了几乎所有常用的小波变换功能。(prominent American Rice University wavelet transform Toolbox, very practical, to achieve almost all commonly used wavelet transform function.)

详细的基于离散小波变换的图像融合matlab程序,可以用于处理任何格式的灰度图像(Detailed based on discrete wavelet transform image fusion matlab procedures, can be used to deal with any format of the gray image)

二代小波harr变换整数小波变换，适合图像处理专业人员参考(Second generation wavelet transform Harr integer wavelet transform for image processing professionals reference)

Fast wavelet transforms and numerical algorithms 1

小波阈值去噪 软阈值去噪和硬阈值去噪的比较(Wavelet thresholding soft thresholding and hard thresholding comparison)

Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously with a smooth reconstructed image. Both contourlets as well as complex-valued dual-tree wavelets are considered for their highly directional representation, while bivariate shrinkage is adapted to their multiscale decomposition structure to provide the requisite sparsity constraint. Smoothing is achieved via a Wiener filter incorporated into iterative projected Landweber compressed-sensing recovery, yielding fast reconstruction. The proposed approach yields images with quality that matches or exceeds that produced by a popular, yet computationally expensive, technique which minimizes total variation. Additionally, reconstruction quality is substantially superior to that from several prominent pursuits-based algorithms that do not include any smoothing

移动窗口二维相关光谱方法matlab的实现，完全是自己参照公式编的哦。。移动窗口二维相关光谱是一种新的二维相关分析方法,它将移动窗口的概念和二维相关分析方法有效地结合在了一起,利用移动窗口将庞大的光谱数据按矩阵分割成若干个便于操作的子矩阵,用二维相关光谱分别处理,将得到的结果综合分析,用以光谱变量和扰动变量为坐标的等高图表现出来,从中可以非常直观地观察出光谱强度在扰动变量方向上的变化,进而找出引起光谱强度突变的特征扰动点。(Moving window two-dimensional correlation spectroscopy method matlab realization, is entirely their own formulas reference the Oh. . Moving window two-dimensional correlation spectroscopy is a new two-dimensional correlation analysis method, it will move the window concept and two-dimensional correlation analysis method is effective to combine together, using the moving window at the huge spectral data matrix is ​ ​ divided into a number of easy to operate a sub-matrix, respectively, using two-dimensional correlation spectroscopy process, comprehensive analysis of the results obtained for the spectral variables, and disturbance variables manifested contour map coordinates, which can visually observe the spectral intensity of the direction of the disturbance variable The change, then find mutations characteristic spectral intensity caused disturbance point.)