小波分解在图像处理 Wavelets

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.)

its c-wavelet transform

对于PCA ，LDA，BIC，EBGM都有很详细的代码。但是需要在LINUX下配置运行。不过代码较有参考价值。(For PCA, LDA, BIC, EBGM have a very detailed code. But the need to configure to run under LINUX. However, a more useful code.)

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.)

53小波变化的vc程序，很详细，有一维和二维，可以对图像进行处理。(53 wavelet transform vc program, very detailed, one-dimensional and two-dimensional image processing.)

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)

基于论文<<Blur Detection for digital images using wavelet transform>>,使用Haar小波变换实现图像模糊度检测。(Based on paper <Blur Detection for digital images using wavelet transform> > , Using the Haar wavelet transform of image blur detection.)

C语言实现一维离散小波变换，通过mallat算法实现对一维信号的快速重构和分解。(C language implementation of a one-dimensional discrete wavelet transform, fast algorithm by mallat one-dimensional signal reconstruction and decomposition.)

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.)

小波分解在图像处理和电能质量分析中应用广泛，本文应用小波分解的方法将高频的暂态信号提取出来，获取暂态信号的特征量，就能够有效地计算暂态信号。(Wavelet decomposition in image processing and power quality analysis is widely used, this application of wavelet decomposition method to extract high-frequency transient signals, to obtain the amount of transient characteristics of the signal, we can effectively calculate the transient signal.)