waveletlegall53

计算小波时间熵的源程序，内容详尽，调试正确，非常有用。计算小波时间熵的源程序，内容详尽，调试正确，非常有用。(Calculate the entropy of the source wavelet time, detailed, debugging is correct, very useful. Calculate the entropy of the source wavelet time, detailed, debugging is correct, very useful.)

数字图像获取, 处理及实践应用源代码——很多有用的图像处理的源代码：图像显示（原图、抖动），图像增强（灰度变换、直方图均衡、多种滤波器、伪彩色增强等），图像复原（运动模糊、逆滤波等等），图像变换（傅立叶变换、快速傅立叶变换、离散余弦变换、沃尔什变换、霍特林变换、小波变换、小波反变换），图像编码（霍夫曼编码、香浓-费诺编码、算术编码、位平面编码等），图像识别。(Digital image acquisition, processing and practical application source code- a lot of useful image processing source code: Image Display (image, jitter), image enhancement (gray-scale transformation, histogram equalization, multi-filter, pseudo-color enhancement, etc. ), image restoration (motion blur, inverse filtering, etc.), image transform (Fourier transform, fast Fourier transform, discrete cosine transform, Walsh transform, Hotelling transform, wavelet transform, wavelet transform), image coding (Huffman coding, Shannon- Fenno coding, arithmetic coding, bit plane coding, etc.), image recognition.)

基于小波变换的随机噪声降噪的matlab 主要运用的方法有软阈值去噪法和硬阈值去噪法(Based on wavelet transform matlab random noise and noise reduction methods are mainly used soft thresholding method and hard thresholding method)

MATLAB实现小波变换中的图像拼接技术，可实现水平拼接(In MATLAB wavelet transform in image stitching technology, can achieve the level of splicing)

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

Wavelet compression algorithm. Start by computing a complete wavelet-transform using the cohen-daubechies-fevereau (2,2) biorthogonal wavelet (which incidentally seems to be the same as used for lossless JPEG2000, but they call it a (5,3)?).

说明：  采用5/3小波提升算法编写的一维和二维信号小波分解与重构程序。给出了图象分解的演示示例。(using 5/3 wavelet algorithm to enhance the one-and two-dimensional wavelet decomposition and reconstruction process. Given the decomposition of images demonstration examples.)

mimo_BP用于十字型阵列雷达，利用匹配滤波理论进行算法仿真(mimo_BP Used for cross-array radar, using matched filter theory for algorithm simulation)

应用Matlab进行小波包对时变谐波分析的代码(Matlab Applications for wavelet packet on time-varying harmonic analysis)

以labview为平台通过小波分析方法对波形进行处理。(Labview as a platform for analysis of the waveform by wavelet processing.)