数字图像处理的基本程序 vc++编写 图像细化 有实例图片

Visual C++ 数字图像处理典型算法及实现(3)-Visual C++ digital image processing algorithms and implementation of a typical (3)

一个关于画图方面的小程序，很有实用性哦 -A small area on the drawing process, is very practical Oh

将彩色图像转换成灰度图像的程序，也可以转换成二值图像。-Color images will be converted into gray-scale image of the procedure can also be converted into binary image.

采用VC++编写，提供一个图像处理的编程平台-Used VC++ Prepared to provide a programming platform for image processing

matlab实现的，神经网络仿真系统，对于想研究神经网络这块东西，很值得去看的东西哦-matlab realization, neural network simulation system, the neural network would like to study this thing, it is worth Oh, look at things. .

反色：通过对图像的处理使图像各种颜色变得和原始图像颜色相反-Anti-color: image processing of the image has become a variety of colors and the original image color contrast

Gray图象灰度处理示例 一个基于DirectX的图象灰度处理示例可是MMX的新作了 转载请注明来源： 开源盛世-源代码下载网 httpwww.vscodes.com -Gray gray image processing based on DirectX example of a grayscale image processing examples But the new MMX reproduced indicate the source : Open source Spirit-source code download network httpwww.vscodes.com

用vc++编程实现图像二值化，设定阈值为122即最大灰度的一半-Vc++ programming with image binarization, the threshold set for the 122 that is half the maximum gray

bmp的打开及简单处理以及保存。 bmp的打开及简单处理以及保存。-bmp opened and the simple handling and preservation. Bmp opened and the simple handlin g and preservation.

：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.