An Introduction to Wavelets

D5/3提升整数小波，可实现图像的无损压缩，包括一维和二维图像整数小波变换-D5/3 integer wavelet upgrade can realize lossless image compression, including the one-dimensional and two-dimensional image integer wavelet transform

这是小波变换的好多算法，有需要的，可以参考-This is a lot of wavelet transform algorithm, there is a need, and can refer to

本程序实现二维灰度图像的小波变换和逆变换。 直接运行本目录下的批处理程序run即可。 用户需自己输入以下参数： 1. 图像文件名(lena.bmp，若使用其它图像请先放入本目录下) 2. 选用的小波名称(本程序中可使用haar及db2-db5) 3. 小波变换的级数。 运行结束后小波变换与逆变换结果分别保存在dec.bmp与rec.bmp中。-This procedure realize two-dimensional gray-scale image wavelet transform and inverse transform. Catalog under the direct operation of a batch process can run. Users need their own, enter the following parameters: 1. Image file name (lena.bmp, if the use of other images, please Add Catalog under) 2. Wavelet chosen name (This procedure can be used haar and db2-db5) 3. Wavelet Transform series. Run after the wavelet transform and inverse transform results are stored in dec.bmp in with rec.bmp.

对输入图像进行预处理后提取目标轮廓，经过归一化处理得到目标形 状的平移、尺度不变的链状表达，再通过小波变换进行多尺度分析；引入Zernike 矩，利用Zernike 矩的特性，实现小波表达的旋转不变性，解决了小波变换对起始点的依赖。-right to import images from pretreatment profile targets, after processing to be a target shape translation, The scale-invariant chain expression, and through the wavelet transform multi-scale analysis; introduction Zernike moment, use Zernike moments, wavelet achieve expression of rotation invariance, solve the wavelet transform the dependence of the threshold.

小波图象去噪综述谢杰成张大力徐文立-Wavelet Image Denoising vigorously Jie Zhang Xu Wenli

给出了在matlab环境下的源代码，经过了上机调试，可以实现小波变换对图像的二次压缩！-given Matlab environment in the source code, after the Machine, can achieve a wavelet transform of the second image compression!

各种数字水印的matlab源代码，包括离散余弦，小波变换等-A variety of digital watermarking matlab source code, including the discrete cosine, wavelet transform, etc.

用于小波变换的图像信号二维频谱分析-for wavelet transform two-dimensional image signal spectrum analysis

基于小波变换的匹配追踪算法,估计极其精确,推荐-Wavelet-Based Matching Pursuit Algorithm

用来分析信号频分量，对信号进行分解。可用于图像、的分解和重构。-Used to analyze the frequency component signal, the signal decomposition. Can be used for images, the decomposition and reconstruction.