dd

说明：  内含多种图像去噪的方法，包括高斯，椒盐噪声等问题(Contains a variety of image denoising methods, including Gaussian, salt and pepper noise and other issues)

粒子滤波器（particle filter）程序，用粒子滤波器跟踪运动物体。(Particle filter (particle filter) process, with particle filter to track moving objects.)

对灰度图像进行水平投影、垂直投影、对角投影其中对角投影是自己编的，已经运行过的(hsdbjhcbj kdjnkdj dhcnkujfhk )

快速角点检测，对学习角点检测同学应该有帮助。(Fast corner detection, detect students learning corners should help.)

量化离散余弦变换系数的程序实现及其效果的检测。过程中使用了8x8的分块方法。首先计算每块的离散余弦变换（DCT)；然后量化了DCT的系数； 最后进行了反离散余弦变换(iDCT). 程序中还可以设定缩放系数。(Quantify the discrete cosine transform coefficients procedure and its effect detection. The process used in the 8x8 sub-block method. First calculate the block discrete cosine transform (DCT), quantization of the DCT coefficient Finally, the inverse discrete cosine transform (iDCT) program can also set the scaling factor.)

基于mind相似性度量的图像配准，配准精度很高。效果不错。(Mind based on similarity measure of image registration, the registration precision is high. The result is right.)

汽车车牌数字识别（上个学期的数字图像处理的课程设计），能运行(Automobile license plate number identification (the last semester of digital image processing course design), can run)

有关指纹识别预处理阶段图像分割的源程序，用matlab言语做的，很好用(The fingerprint identification preprocessing stage image segmentation of the source, using MATLAB language to do, very good use)

基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类，即把收敛到同一点的起始点归为一类，然后把这一类的标号赋给这些起始点，同时把包含像素点太少的类去掉。然后，采用阈值化分割的方法对图像进行二值化处理 (Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixels, that is, to converge to the same point as a starting point to the category and then assigned to this type of labeling of these starting points, at the same time to contain too few pixels to remove the category. Then, using thresholding segmentation method of binary image processing)

这是图像处理中HSV课件颜色特征提取（将H5等份，S,V分量各三等份）MATLAB源码。(This is the image processing in HSV color feature extraction software (to be H5 equal, S, V component of the third class) MATLAB source.)