基于fastICA的独立分量分析算法中的核心算法

基于小波域的隐马尔可夫树模型的图像去噪方法的实现代码。-Based on the Wavelet Domain Hidden Markov Tree Model Image Denoising realize the code.

：由于许多传统的去噪方法在强背景噪声情况下提取声音信号的能力变弱甚至失效， 提出 应用独立成分分析( I C A) 方法对声音信号进行特征提取， 并证明了这种 I C A 变换能增强语音和音 乐信号的超高斯性． 在此基础上， 应用 I C A基函数作为滤波器， 通过阈值化的去噪方法对含有强高 斯背景噪声的声音信号进行去噪仿真实验． 结果表明， 本方法明显优于传统的均值滤波和小波去噪 方法， 为强背景噪声下弱信号的检测提供 了新的途径．-: As many of the traditional de-noising method in case of strong background noise, the ability to extract the voice signal even weaker failure, the application of independent component analysis (ICA) method of voice signal feature extraction, and prove that this transformation can be enhanced voice ICA and music of super-Gaussian signals. On this basis, the application of ICA basis function as a filter, through the threshold of the denoising method of Gaussian background noise contains strong voice signal denoising simulation. The results show that this method is obviously superior to the traditional mean filtering and wavelet denoising methods for the strong background noise under the weak signal detection provides a new way.

在VC++平台上实现图形图像的百叶窗效果-In VC++ platform to achieve the effect of graphic images of blinds

数字图像腐蚀程序。参数中有一个BOOL变量， 为真时，表示在水平方向进行腐蚀运算，否则在竖直方向上进行腐蚀运算。-digital image corrosion process. Parameters have a BOOL variable to true, in the horizontal direction corrupting computation, Otherwise, the vertical direction on erosion.

这是ＤＥＬＰＨＩ编程写的一个有关图象处理的的图象的反相和缩放-This is a program written in the image processing of the image and zoom in RP

图像处理算法全集，包含很多经典的算法，非常实用，欢迎下载-The Complete algorithms of image processing ，Contains a lot of classical algorithms, very useful, please download！

利用Delphi实现高速屏幕图象传输的例程序.-Delphi realize the use of high-speed image transmission Example screen procedures.

网页转化为图片软件――WebToImange-Web page into a photo software- WebToImange

完成图像RGB到HSV的转换，比较自定义函数转换和使用opencv提供函数直接转换的结果。可用于研究H，S，V分量的范围等-Image RGB to HSV conversion, more-defined functions and use the conversion function opencv provide direct conversion results. Can be used to study H, S, V component of the scope of

On gradient-corrected and regional watershed segmentation algorithm combined