uuity7i

图片处理 去噪音，去模糊为了实现较好保留图像边缘特征的有效去噪,提出了一种基于边缘检测的Contourlet 变换去噪方法(Picture Deal)

一个有关边缘检测 robert sobel FFT傅里叶变换等算法的demo(a demo using VC++ that implements the algorithms of edge detection and FFT)

视觉测量中编码点与非编码点的匹配的方法实现(Vision measuring, coding point and the coding point matching )

可以打开各种图像格式，并显示，很好很强大(Can open a variety of image formats)

RAC法标定程序，适用于单目摄像机的线结构光的标定(The RAC calibration method procedure applies to line structured light calibration)

快速距离变换的程序，是在外国人的一个程序上小改了一下，vs2008下的控制台程序，可以直接设置断点调试(Fast distance transform procedure is a procedure in the foreign small change a bit, vs2008 console under the program, you can set breakpoints directly)

基于vc++6.0的SURF算法的程序代码，可以直接运行(Based on the SURF algorithm for vc++6.0 program code can be run directly)

KLT point match:Detection and Tracking of Point Features.

图像处理实习（针对遥感影像），包含许多经典的图像处理功能，比如多种植被指数计算、小波变换、镶嵌、图像分类等(Image processing internship (for remote sensing images), contains many classic image processing functions, such as a variety of vegetation indices, wavelet transform, mosaic, image classification, etc.)

EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤： （1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声； （2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向； （3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大； （4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。 (Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of the other edge detectors requires urther processing to generate potential object boundaries, which may not even be possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.)