MODEL4

本程序采用了特征线法计算管道阀门关闭时的水锤(This program uses a water hammer characteristic line method to calculate the pipe when the valve is closed)

这是一个简单的掌纹识别系统，运用了PCA算法，可以做到较快的运算。(This is a simple palmprint recognition system that uses the PCA algorithm to achieve faster calculations.)

说明：  Donoho提出的小波阀值去噪的基本思想是将信号通过小波变换（采用Mallat算法）后，信号产生的小波系数含有信号的重要信息，将信号经小波分解后小波系数较大，噪声的小波系数较小，并且噪声的小波系数要小于信号的小波系数，通过选取一个合适的阀值，大于阀值的小波系数被认为是有信号产生的，应予以保留，小于阀值的则认为是噪声产生的，置为零从而达到去噪的目的。尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点。(The basic idea of wavelet threshold de-noising proposed by Donoho is that the wavelet coefficients generated by the signal after passing through the wavelet transform (Mallat algorithm) contain the important information of the signal. After the wavelet decomposition, the wavelet coefficients of the signal are larger, the wavelet coefficients of the noise are smaller, and the wavelet coefficients of the noise are smaller than the wavelet coefficients of the signal. By selecting a suitable threshold, the wavelet coefficients of the noise are larger than the valve The wavelet coefficients of values are considered to be generated by signals, which should be preserved. The ones less than the threshold are considered to be generated by noise, which is set to zero to achieve the purpose of denoising.)

光流法实时实现的文献及代码，2012发表于cvpr，200*200的图像，每秒可达200帧，2012_CVPR_Lip-motion events analysis and lip segmentation using optical flow(Optical flow method to achieve real-time literature and code, 2012 published in cvpr, 200* 200 images per second, up to 200, 2012_CVPR_Lip-motion events analysis and lip segmentation using optical flow)

说明：  对图像进行灰度处理，乘除处理法处理，加法处理，减法处理(Gray scale, multiplication and division of image)

扇束反投影滤波,这是一个通过反投影滤波法重建CT图像的 matlab程序(dgfgdg dgrehj )

对比了常见的几种去噪方法，含中值滤波，均值滤波，维纳滤波，高斯滤波，以及三种形态学滤波（一般的，改进的，多结构元素形态学滤波）(Comparison of several common Denoising containing median filtering, mean filtering, Wiener filtering, Gaussian filtering, as well as three morphological filtering (generally improved, multi-structural elements morphological filtering))

说明：  此算法使用于单波段或者多波段图像中的非监督异常检测，性能很好~(The algorithm used in single-band or multi-band image unsupervised anomaly detection, performance very good ~)

说明：  图像形态学处理，图像腐蚀，图像膨胀，图像细化，边缘检测(Morphological image processing, image corrosion, image expansion, image thinning, edge detection)

各种边缘检测程序，包括2Sobel算子边缘检测， Prewitt算子边缘检测，Roberts算子边缘检测， Laplace算子边缘检测，Canny算子边缘检测 (Edge Color)