ransetideshuliangtongji

老外写的程序，可对三角形进行渲染，有详细的算法介绍。非常棒(A good Triangle Renderer Project，with detailed introduction.)

说明：  去除图像中的横向条纹，能有效恢复出原始图像(remove images of horizontal stripes, can be effectively restored from the original image)

Sobel算子就是一种基于方向导数掩模求卷积的方法。通过边缘检测算子可以检测到每个像素的领域并对灰度变化率进行量化，也包括方向的确定。该代码是基于sobel算法的检测程序。(Sobel operator is a directional derivative mask and convolution methods. To each pixel and gray level in the field rate of change can be detected through the edge detection operator to quantify, including direction. The code is based on sobel algorithm testing procedures.)

用双线性插值法实现的图像缩放，内有详细的使用说明。非常好用(Bilinear interpolation method used to achieve the image scaling, which has detailed instructions. Very easy to use)

sijiequzao 是台雪城老师的四阶去噪模型代码； subspace clustering accuracy of the cod 是子空间聚类正确率代码； TVdual 是ROF模型的原始对偶算法代码； TVH-1fj 是TV_H-1图像分解模型代码； TVl1fj 是TV_L1图像分解模型代码。(" Sijiequzao" is the teacher' s desk Syracuse Fourth Order denoising model code " subspace clustering accuracy of the cod" subspace clustering is the correct rate codes " TVdual" original ROF model dual algorithm code " TVH-1fj" is TV_H-1 image decomposition model code " TVl1fj" is TV_L1 image decomposition model code.)

天津工业大学课程设计，内容包含vs2010对图像的灰度化，二值化，边缘检测。包含单纯c语言编写的对图像的灰度化，二值化，边缘检测的一个.C文件，可以直接用vc6.0运行，也可以直接在DSP上运行，还包含一份详细的设计报告。(Tianjin Polytechnic University curriculum design, content includes vs2010 grayscale image binarization, edge detection. Contains pure c language for image graying, binarization, edge detection is one. C file that can be run with vc6.0 can also be run directly on a DSP, also contains a detailed design report.)

控制测量是测绘专业的基础课程，这个课件是武汉大学老师编的课件，很实用(Control measurements are mapping the professional foundation courses, this courseware is Wuhan University teachers series courseware, very practical)

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

说明：  一种自适应的图像去噪方法，MATLAB实现(An adaptive image denoising method, matlab implementation)

自己写的Normalized Cut图像分割，聚类程序，程序非常清晰，花了很长时间调试。(Normalize Cut)