图像匹配，将两幅不同的角度拍的图像的对应点都找到as

说明：  小波分析增强滤波。小波变换的原理类似傅里叶变换，只是把三角函数基换成了小波基。与傅里叶变换不同，小波变换有两个变量：scale和translation。scale控制小波函数的收缩，其导数即为频率，translation控制小标函数的平移，平移量对应时间。通过信号的伸缩平移，可以得到某种重合情况，这样积分也会得到一个极大值，不同的是，得到频率成分的同时，还可以知道该频率的时间位置。(Wavelet analysis enhances filtering.The wavelet transform works like the Fourier transform, except that the trigonometric basis is replaced by a wavelet basis. Unlike the Fourier transform, the wavelet transform has two variables: scale and Translation. Scale controls the contraction of the wavelet function, its derivative is frequency, translation controls the translation of the small scale function, and the translation corresponds to the time. By stretching and shifting the signal, you can get some kind of coincidence, so that the integral will also get a maximum, but the difference is that when you get the frequency component, you can also know the time position of that frequency.)

将原图与一幅模板图像进行计算相关 以图像显示相关函数(The original image and a template image to calculate correlation functions related to image display)

本文件包含连通区域标记以及面积测量的matlab源代码(This document contains the connected component labeling, and area measurement of the source code matlab)

说明：  基于最小变分方法的快速图像复原方法，图像复原质量不变的情况下，加速算法的效率。(Image restoration based on Total Variation.)

实现基于混合高斯模型的运动目标检测算法的仿真(Achieved based on Gaussian mixture model simulation of moving target detection algorithm)

目标跟踪matlab源代码，通过当前帧预测区域的信息同背景图像的信息的内容相差，可以很好的实现运动目标的跟踪。(Target tracking matlab source code, through the regional information predict the current frame image with the background information on the contents of the difference, you can achieve a good tracking of moving objects.)

说明：  自组织神经网络SOM的算法，经过调试可以用(Self-organizing neural network SOM algorithm can be used after debugging)

K均值图像分割，读入彩色图片，输出区域分割后的图片(K-means image segmentation, read full-color photographs, the output image after the region segmentation)

在ENVI中利用此程序可将多光谱影像拆分为单个波段。(In ENVI, multi-spectral images can be divided into single bands by using this program.)

APG算法，加速近端临近点算法，通过对子问题的调整，计算速度很快(APG algorithm, accelerated near the proximal point algorithm, by adjusting the sub-problems, fast calculation)