wavelet

中值滤波源程序，非常好用。程序有说明很容易看懂！(median filtering source, very handy. Note procedure is easy to read!)

在理解了离散小波变换的基本原理和算法的基础上，通过设计VC程序对简单的一维信 号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波和Haar小波变换，从而得到小波分解系数；再通过改变分解得到的各层高频系数进行信号的小波重构达到消噪的目的。在这一程序实现的过程中能直观地理解信号小波分解重构的过程和在信号消噪中的重要作用，以及在对各层高频系数进行权重处理时系数的选取对信号消噪效果的影响。(In understanding the basis of discrete wavelet transform basic principles and algorithms, through the design VC program Daubechies wavelet, Morlet wavelet and Haar wavelet transform after a simple one-dimensional signal plus a Gaussian white noise, resulting wavelet coefficients wavelet reconstruction signal again by changing the layers to achieve high-frequency coefficients decomposed noise cancellation purposes. Can intuitively understand wavelet decomposition and reconstruction process and an important role in signal de-noising in the process of implementation of this program, and in the high-frequency coefficients when the weight of the layers selected for signal processing coefficients denoising affected.)

小波变换的数字水印算法,附有论文和源程序.(Wavelet Transform Digital Watermarking Algorithm with thesis and source code.)

its c-wavelet transform

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)?).

利用小波变换进行改进阈值信号去噪 (Improvement threshold signal denoising using wavelet transform)

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)

< VISUAL C++ 小波变换技术与工程实践>>书中所附程序:小波变换在视频编码压缩中的应用(<VISUAL C++ Wavelet transform technology and engineering practice of>> the book accompanying procedures: Application of wavelet transform in video coding compression)

vc实现虚拟示波器，没有测试过不知道能用吧(vc virtual oscilloscope not tested do not know can)

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.)