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用CUDA并行处理方法改写的图像降噪算法，包括KNN,NLM,以及改进的NLM方法。配置环境适合VS2010+CUDA5.0,对使用CUDA的同学来说是很好的教材。(Image denoising algorithms including KNN,NLM and refined NLM run on CUDA, useful demo for who learns CUDA based parallel programming.)

DCT 数字水印 VC源代码 DCT 数字水印 VC源代码(DCT digital watermarking VC source code DCT digital watermarking VC source code)

经典的文本水印算法，实现了别人实现不了的功能，希望大家有所用！(The classic text watermarking algorithm to achieve the functions of others fail to realize, I hope you all have a use!)

一种新的彩色图像去噪与增强模型(A new color image denoising and enhancement model)

SURF 图像特征点快速提取法还有描述，可用于迅速匹配两张图片中的特征点(SURF image feature points extraction method also described fast, can be used to quickly match the image feature points in the two)

运用openCV编写的C++图像色彩转移程序，原理是先转化到Lab图像，再保持L不变调整图像的a、b分量的均值跟方差。(Using openCV prepared C++ image color transfer process, the principle is first converted to Lab image, and then adjust the image to keep L constant a, b, with the mean variance component.)

医学图像处理方面的一些基础算法，VC环境下编译的一个非常好的程序框架(Medical image processing, some of the basic algorithm, VC compiled under the framework of a very good program)

打开bmp位图文件 彩色转灰阶 直方图均衡 直方图规定 灰阶线性化(Open the bmp grayscale bitmap image binarization functions connected domain extraction features)

说明：  本课题的主要内容是图像预处理,它主要从摄像头中获取人脸图像然后进行处理,以便提高定位和识别的准确率.该模块主要包含光线补偿、图像灰度化、高斯平滑、均衡直方图、图像对比度增强，图像预处理模块在整个系统中起着极其关键的作用，图像处理的好坏直接影响着后面的定位和识别工作,内有源代码和全部论文资料(this issue is the major content of image preprocessing, mainly from the camera to obtain images Face then, in order to improve the recognition and positioning accuracy. The module consists mainly of light compensation, Grayhound, Gaussian smoothing, balanced histogram, image contrast enhancement, image pre- processing module in the system plays a crucial role in image processing will have a direct impact behind the positioning and identification, within Active code and all papers information)

photoshop的各个效果的详细介绍，方便研究photoshop的各种算法，值得一看啊！！(photoshop detailed description of the various effects, photoshop various algorithms to facilitate research, worth ah! !)