SVDdenoise

基于数学形态学的图像颗粒度分析算法，先去噪再求面积然后绘制颗粒度函数。(based on mathematical morphology particle size analysis algorithms, first try to de-noising area before drawing particles function.)

说明：  用光流法估计图像的运动，基于像素点的算法(Light flow method estimates the image campaign, pixel-based algorithm for point)

画矩形的代码，包含各种算法，具体的自己看吧，这是图形处理的作业之一(Draw a rectangle of the code, contains a variety of algorithms, specifically for yourself, this is one of the graphics processing jobs)

针对现有方法存在的隐藏容量低、操作不灵活的缺陷，文章提出了一种基于无损压缩的加密图像可逆 信息隐藏算法。(In view of the defects of low hiding capacity and inflexible operation of the existing methods, this paper proposes a reversible information hiding algorithm for encrypted images based on lossless compression.)

vc++6.0进行编程实现对图像的平移处理(vc++6.0 program to achieve the translation of the image processing)

提出了一种基于非下采样Contourlet 变换的自适应图像去噪方法 首先对噪声图像进行非下采样Contourlet 变换，得到各 个尺度各个方向子带的系数，再根据该系数的能量自适应地调整去噪阈值 实验表明，与Contourlet 多尺度阈值去噪 Contourlet 自 适应阈值去噪相比，该方法在保留图像边缘细节的同时，能提高图像的PSNR 值，减少了Gibbs 现象(A new adaptive method of image de-noising based on NonSubsampled Contourlet Transform （NSCT）is presented.Firstly， the noisy image is decomposed into a set of multiscale and multidirectional frequency subbands by NSCT， and then the threshold is adapted automatically according to the energy of subband coefficients.Compared with the multi-scale threshold using contourlet transform and using adaptive threshold based on contourlet transform， the simulation results show that the performance of this method is superior in PSNR， meanwhile it can maintain the image edge and reduce the Gibbs phenomen)

检测道路边缘，利用道路的平行线特性，来检测道路所在直线。(Detect edges of the road, the road parallel to the line features to detect the road where the straight line.)

matlab6.5图形图像处理源程序 部分内容 第二章压缩包 (matlab6.5 )

说明：  基于Kmeans算法的图像分割，一般Kmeans是数据挖掘中用来聚类的，本试验利用图像中的灰度值作为Kmeans算法的原始点，进行图像分割(Kmeans algorithm based on image segmentation, data mining in general Kmeans is used to clustering, the trial use of the image gray value as the original algorithm Kmeans spots for Image Segmentation)

包括最原始的分数阶微分方法，自适应分数阶微分法，非整数步长的方法。对学习分数阶微分的人是个很好的资料代码。(It includes the most original fractional differential method, adaptive fractional differential method, and non integer step length method. It is a good data code for people learning fractional differential.)