2-D-DWT

我实现的离散小波变换，可直接运行，采用三级变换(Discrete wavelet thransform)

超声图像去噪，基于小波变换的通用超声图像去噪，能够有效的去除相干斑(Ultrasound image denoising based on wavelet transform common ultrasound image denoising, can effectively remove speckle)

小波变换、小波逆变换代码，数字信号处理领域常用(Wavelet transform, wavelet inverse transform code, digital signal processing used)

小波变换的模极大值重建信号源程序 非常具有参考价值(wavelet transform modulus maxima reconstruction signal source is a very valuable reference)

数字信号处理的c++库，很好的资源，作者很牛，包括数值计算与常用的信号处理分析,例如FFT、小波变换、功率谱估计等(Digital Signal Processing c++ library, a great resource,including numerical analysis and common signal processing，such as FFT, wavelet transform, power spectrum estimation)

双树复数小波变换的滤波程序,在所有小波变换的程序中，该程序采用双变量模型能很好完成去噪功能(dual-tree complex wavlet transform is a good inshift wavelet transform)

本程序是在labview中利用小波变换理论检测回波(This procedure is in the use of wavelet transform theory labview echo detection)

离散小波变换的简单程序，适合初学者学习，附有通用函数。(Simple procedures discrete wavelet transform, suitable for beginners to learn, with common functions.)

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

利用小波变换实现和直方图均衡化相对比的图像的增强与分割.应该比较有用.分割也采取了几种技术的对比(using wavelet transform and histogram equalization relative ratio of image enhancement and segmentation. Be more useful. Pm cutting has taken several technical contrast)