RGB格式图像转YUV

转：https://blog.csdn.net/jinshengtao/article/details/26278725 混合高斯背景建模是基于像素样本统计信息的背景表示方法，利用像素在较长时间内大量样本值的概率密度等统计信息(如模式数量、每个模式的均值和标准差)表示背景，然后使用统计差分(如3σ原则)进行目标像素判断，可以对复杂动态背景进行建模，计算量较大。 在混合高斯背景模型中，认为像素之间的颜色信息互不相关，对各像素点的处理都是相互独立的。对于视频图像中的每一个像素点，其值在序列图像中的变化可看作是不断产生像素值的随机过程，即用高斯分布来描述每个像素点的颜色呈现规律单模态(单峰)，多模态(多峰)(Gaussian mixture background modeling is a background representation method based on the statistical information of pixel samples. Statistical information such as the number of patterns, the mean and standard deviation of each pattern are used to represent the background. Statistical difference (such as 3_principle) is used to judge the target pixel. Complex dynamic background modeling has a large amount of computation. In the Gaussian mixture background model, it is considered that the color information between pixels is uncorrelated and the processing of each pixel is independent of each other. For each pixel in a video image, the change of its value in a sequential image can be seen as a random process that produces pixel values continuously, i.e. Gaussian distribution is used to describe the regularity of color rendering of each pixel in single mode (single peak) and multi-mode (multi-peak).)

图像质量评价经典算法，ssim算法评价图像质量好坏程度的度量(Image quality assessment of the classical algorithm, SSIM algorithm.A measure of the degree of image quality )

jpeg图像压缩和解压缩过程，使用的哈弗曼表包含于程序中，内有详细的文件说明(jpeg image compression and decompression process, the use of Huffman tables included in the program, with detailed documentation)

自行设计的概率密度函数统计方法，代替ksdensity函数(Probability density function of self-designed statistical methods, instead of ksdensity function)

KSVD&&OMP处理图像的程序，有演示效果(KSVD&&OMP )

直线检测 Visual C++编写 用于图像处理(line segment detection)

北航图像处理demo，目前集成了从色彩转换、彩色图像处理、灰度图像处理、二值图像处理、阈值分割、边缘检测、数学形态学方法、等多个组件(Northern image processing demo, now integrated from the color conversion, color image processing, gray-scale image processing, binary image processing, thresholding, edge detection, mathematical morphology, and many other components)

三种改进的图像增强算法，包括改进的类拉普拉斯增强算法，混合式MSRCR彩色图像增强算法，区域自适应反锐化掩模图像增强算法。(Three improved image enhancement algorithms, including improved classes, Laplace enhancement algorithms, the hybrid MSRCR Color Image Enhancement algorithm, region adaptive unsharp mask image enhancement algorithms)

用于图像中边缘检测的重要算法，radon变换，该MATLAB程序实现了radon变换，直接确定图像中边缘位置和边缘强度(Radon convert)

sift图像处理的一个测试的代码，他是用C++写的 用到了opencv中的一些函数(sift image processing as a test of the code, he wrote with C++ uses some of the opencv function)