CS

能够实现视频处理，利用MATLAB实现的VIEB算法，简单有效(To achieve video processing, using MATLAB implementation of the VIEB algorithm, simple and effective)

给出了灰度图像（256*256大小）的三层高斯和拉普拉斯金字塔分解的程序和实现方法。内容包括：1.matlab源码，亲身实践，因为论文需要，自己专研的。完全可用。2.国外最先最权威的关于分解原理介绍的文章。以上两个内容中都有本人的悉心注释和思路总结，内容详尽。3.图示结果(code and principle of laplacian pyramid decomposition of a gray scale image are provided in the article.Contents are given in detail including the notes and usage. )

说明：  图像识别的matlab程序实现，基于神经网络的图像识别(Image recognition matlab program implementation, image recognition based on neural networks)

这个是我自己编写和修改的圆特征检测的程序，能同时求取多个圆的圆心和半径信息。并且文件中有测试图片，直接运行就可以出结果。(The files can detect multi circles in one image at the same time，circle center and R information can be obtained.)

实现图像识别，基于小波变换实现图像特征提取，然后神经网络进行训练(The image recognition is realized, the image feature extraction is realized based on wavelet transform, and then the neural network is trained.)

加权核范数最小化应用于图像处理的代码，很实用，且是图像处理领域很新的方法源码，所以该方法效果很好，希望对大家有用。(Nuclear weighted norm minimization codes used in image processing, it is useful, and it is a new image processing method for the source, so that this method works well, want to be useful.)

图像处理源程序，实现二值化变换，经一幅图像灰度化后，变成二值化图像，包括大津法、最大类间方差法、一般阈值法、及文本识别最有用的Niblack法(Image processing program and realized binarization transformation, after by a gray-scale image into binary image, including the Otsu method, Otsu method, the general threshold, and text to identify the most useful Niblack method)

输入一幅图像，用传统的算子方法进行检测与用形态学腐蚀之后使原图像与腐蚀后的图像相减得到图像边缘进行比较(The Mathematical Morphology Image Edge Detection Based on MATLAB)

说明：  增广拉格朗日乘子法ALM算法是机器学习中十分常用且有效的一种优化算法，经常用于低秩和稀疏问题的优化求解中，这个包是增广拉格朗日乘子法的matlab代码(ALM algorithm of augmented Lagrange multiplier method is a very common and effective optimization algorithm in machine learning. It is often used in the optimization of low rank and sparse problems. This package is the matlab code of augmented Lagrange multiplier method)

生成四副条纹图，进行四步相移，并且进行相位解包裹，并以图片形式输出结果(Generate four fringes, were four-step phase shift and phase unwrapping, and output as a picture)