image_stitching

利用各种向量函数实现matlab中对于图像特征的识别(image recognition)

显示JPEG图片的源码.........................................(show jpeg picture)

主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间。给定 n 个变量的 m 个观察值，形成一个 n ′ m 的数据矩阵， n 通常比较大。对于一个由多个变量描述的复杂事物，人们难以认识，那么是否可以抓住事物主要方面进行重点分析呢？如果事物的主要方面刚好体现在几个主要变量上，我们只需要将这几个变量分离出来，进行详细分析。但是，在一般情况下，并不能直接找出这样的关键变量。这时我们可以用原有变量的线性组合来表示事物的主要方面， PCA 就是这样一种分析方法。(Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical method to grasp the principal contradiction of things, it can be resolved diverse things out the main factors, revealing the essence of things, simplifying complex problems. The purpose of calculating the main component of high-dimensional data is projected to a lower dimensional space. Given n variables of m observations, forming an n ' m of the data matrix, n is usually large. For a complex matters described by several variables, it is difficult to know, so if you can grab something to focus on key aspects of analysis? If the main aspects of things just reflected on several key variables, we only need to separate out these few variables, for detailed analysis. However, in general, does not directly identify this critical variables. Then we can represent the major aspects of things with a linear combination of the original variables, PCA is one such analysis.)

文字可视化，对于给定的文本，输出可视化效果的程序。(word visualization)

sar滤波中最经典的频率域滤波算法.效果也不错.(sar filtering of the most classic frequency domain filtering algorithm. effect is not bad.)

基于混合高斯的运动目标检测程序已经相应的文章！非常值得借鉴！(Gaussian mixture-based moving object detection procedures have been the appropriate article! Well worth learning!)

红外图像细节增强仿真，其中使用双边滤波器进行图像分层。带测试源数据。(Infrared image detail enhancement, with test source data)

Image to be embedded into an image

该源程序构建了车牌识别系统，里面包含相应的模板，可以直接运行(The source code license plate recognition system was constructed, which contains the appropriate template, you can directly run)

KPCA是一种PCA的改进方法,很值得一看,很实用!(KPCA is an improved method of PCA, it is worth a visit, it is useful!)