Wavelet transform routines

基于小波和统计特性的自适应图象增强-based on wavelet and the statistical characteristics of adaptive image enhancement

在图像中嵌入水印的matlab源代码（cox算法，cdma方式，以及小波变换方式），及嵌入结果图片-image in the watermark embedded in the source code Matlab (cox algorithm, cdma, and the wavelet transform mode), and the results of embedding Photo

基于图像抽取和小波变换的压缩方法，很值得参考-Extraction and image-based wavelet compression method, it is worth considering

呵呵 额呵呵呵呵 额呵呵呵呵 额呵呵呵呵 额呵呵呵呵额-hehe

提升方法实现小波变换，大大提高了小波变换的速度，并且不会降低图像恢复质量，很有价值的算法实现-upgrade method wavelet transform and greatly enhance the speed of wavelet transform, and will not reduce the image restoration quality, great value Algorithm

该代码为在c语言环境下的基于小波变换的图像处理-The code in c language environment based on wavelet transform image processing

给出了小波变换的具体java实现，小波变换的java程序，共包括waveletgen.java 和transformation.java-given wavelet transform to achieve specific java, java wavelet transform procedures, it includes waveletgen.java and transformation.java

关于二维小波变换的程序 [精华] 说明：此算法重在概念，速度并不是很快。因为FOR循环的缘故。此程序从循环矩阵的观点出发，把圆周卷积和快速幅里叶变换建立了联系。实现了分解和无失真重构。它只做了一层分解，即将256x256图形分解成为64x64的四个图形，避免了使用WKEEP()的困惑。主要思想为用小波滤波器族构造正交阵W,变换写为B=W*A*W ,反变换为：A=W *A*W,这与所有正交变换无异。W为循环正交矩阵，因此可用FFT实现快速运算，难点就在重构矩阵上。若用矩阵概念明确，一个共扼转置可以搞顶。但FFT的使用必须找到与分解序列的关系。-on Wavelet Transform procedures [best] Note : This algorithm important concept is not speed quickly. Because FOR cycle nowadays. This program cycle from the point of view of Matrix, circular convolution and fast Fourier transform is established links. To achieve the decomposition and reconstruction without distortion. It only had one decomposition, 256x256 graphics will be 64x64 decomposition of the four graphics, avoiding the use of WKEEP () confusion. The main idea of using wavelet filter generator orthogonal array W, write to transform B = W* A* W, anti-Transform : A = W* A* W, which is orthogonal transformation all the same. W cycle orthogonal matrix, can be used to achieve rapid FFT computation, on the dif

小波变换的一些源程序-wavelet transform some source

基于LMS（最小均方误差算法）自适应滤波的信源，基于Matlab