fft015

基于matlab程序对声音信号进行去噪处理，通过小波包处理及小波分析结合(Matlab program based on the sound signal denoising by wavelet packet processing and wavelet analysis combined)

wavelet analysis of an image

wavelet transform,continuous wave let transform,discrete wavelet transform

说明：  shearlet变换matlab工具箱，可用于图像降噪、融合(Shearlet transform matlab toolbox can be used for image denoising and fusion)

说明：  有小波分解求小波熵，还有小波包技术求解信号特征，适应与分析脑电信号特征(Seeking a wavelet decomposition wavelet entropy, and wavelet packets technique to solve the signal characteristics, and analysis of EEG characteristics of adaptation)

基于小波和插值的超分辨率图像重建算法，通过插值后将小波分解应用于图像中，再通过逆变换得到重构图像(And interpolation based on wavelet super-resolution image reconstruction algorithm by interpolating the image after the wavelet decomposition used, then the reconstructed image through the inverse transform)

小波基contourlet变换 其中包含spiht编码 去噪 纹理识别(Wavelet transform contourlet transform includes SPIHT coding and denoising texture recognition.)

This is a wavelet program.

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

可用于曲波变换的工具箱，用于含噪声的图像的去噪过程,图像分解，有例子可直接运行。只可用于学术研究目的。(the Latest curvelet transform lab tool ，Non-commercial research use for Academics. Image decomposition, there are examples can be run directly.)