20140521

db53小波的verilog硬件实现源码(Wavelet db53 Verilog hardware source)

关于利用离散余弦变换DCT的jpeg压缩的matlab源程序，简单实用，也有注释，很好读。(on the use of discrete cosine transform DCT jpeg compression Matlab source, simple and practical, the Notes have a good time.)

离散小波变换是指在特定子集上采取缩放和平移的小波变换，是一种兼具时域和频域多分辨率能力的信号分析工具。此变换运用可以缩放平移的小波代替固定的窗进行计算分析，主要应用于信号编码和数据压缩。(Discrete wavelet transform refers to the specific subset take scaling and translation on the wavelet transform, is a kind of multi-resolution ability both time domain and frequency domain signal analysis tool. This transformation can use zoom translational wavelet calculation and analysis instead of the fixed window, mainly used in signal coding and data compression. )

离散小波变换在图像处理去噪中的应用 经典文献 IEEE的(ECG signal compression using 2-D DWT Hermite coefficients)

小波神经网络,实现曲线拟和，数据分类，故障诊断，学习速度快于传统BP。(Wavelet neural network, and realize curve fitting, data classification, fault diagnosis, learning faster than the traditional BP.)

Fast wavelet transforms and numerical algorithms 1

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.)

主要讲述小波变换在信号分析和图像处理中的应用，英文版。(Wavelets applications in signal and image processing)

its c-wavelet transform

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