DrawArcTest

说明：  热电厂CAD图纸资料，在CAD软件中绘制(Thermal power plant CAD drawings)

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.)

pca算法，用于数据降维，注释非常详细清晰，(PCA algorithm, for data dimensionality reduction, clear and very detailed notes,)

plug in to select random polygons in xsi

用于图象的复原处理，可以对多张同样角度拍摄的图片进行分析，得到清晰的放大图． superresulution(Rehabilitation treatment for the image can be more than the same angle picture taken for analysis have been given clear Enlargement. superresulution)

VisualC++数字图像处理技术详解第2版光盘-第三章(VisualC++ digital image processing technology Detailed Version 2 CD- Chapter 3)

说明：  能实现图像的分割和识别,能够区分开近似颜色区域的影响(this code can perform image crop and recongition)

说明：  对于一些图像来说，常用的边缘检测算法有时候无法设立合适的阈值将它们的梯度较小的模糊边缘检测出来。为了解决这个问题，有两种解决方法：将图像方差标准化，拉大模糊边缘的梯度值，或通过设置sigmoid函数，将像素所在区域的信息传递到梯度值中去，对其进行调整，就能找到合适阈值，有效地将模糊边缘提取出来。本程序把这两种算法实现并与与传统算法进行了比较。(For some images, the commonly used edge detection algorithm sometimes can not be an appropriate threshold for the gradient of their smaller fuzzy edge detected. To solve this problem, there are two solutions: the image variance standardization, widening the fuzzy edge of the gradient value, or by setting the sigmoid function pixel region to disseminate the message to the gradient values to adjust, on the can find a suitable threshold, effectively extracted fuzzy edge. This procedure of these two algorithms with the traditional algorithm.)

说明：  裁剪shape文件，使用idl编程实现，就是一个功能，编译以后可以直接调用这个函数(Clipping shape file, using idl programming, is a function, after compiling can directly call this function)

说明：  IEEE_SSR标准PSCAD算例，实用算例亲测有效(An example of IEEE SSR standard PSCAD)