datamining

二维EMD程序，这是利用最新的插值函数，个比较经典的二维经验模式分解程序代码，适用于图像的特征提取和分解((A two-dimensional EMD algorithm, the author is Anna Linderhed, her Ph.D. research topic is bidimensional EMD and wavelet transform))

基于Harris角点检测的图像拼接matlab实现， 主要内容包括Harris角点检测，NCC,RANSAC以及2幅图像的拼接(A image mosaicing algorithem which based on Harris corner feature detection achieved in matlab. The main contents include the Harris corner detector, the NCC, the RANSAC and two image mosaicing)

说明：  实现了基于关键像素点的FLICM图像分割算法，关键像素由局部最大值方法提取。(A FLICM image segmentation algorithm based on key pixels is implemented. Key pixels are extracted by local maximum method.)

分数阶B样条小波用于图像去噪的matlab程序。(B fractional spline wavelet for image denoising matlab program.)

基于多尺度MRF模型的图像分割算法。使用提升小波对原始图像进行分解，使用ICM算法进行分割处理(Multi-scale MRF model based image segmentation algorithm. The original image using lifting wavelet decomposition, the use of ICM segmentation algorithm)

混合像元分解，是定量遥感中非常重要的组成部分之一，在反演地表参数时是必须要考虑的因素之一，文中罗列了分解的一些方法。(mixed pixel decomposition, is the quantification of remote sensing very important component of one of the the inversion of surface parameters is to be considered one of the factors, the paper listed some of the decomposition method.)

说明：  改进了Criminisi算法，采用P-laplace算子作为数据项进行优先级计算，并有计算PSNR的功能(Improved Criminisi algorithm, using P-laplace operator as data items priority basis, and have calculated the functions of PSNR)

isomap matlab的实现源程序，使用时，需要添加主程序。(isomap Matlab implementation source program, when used, need to add the main program.)

用一维小波变换进行图像去噪处理，有较低的计算复杂度，提高效率和计算速度。(Victoria with a wavelet transform image denoising, lower computational complexity, increase efficiency and speed.)

背景减除的完整算法，《A Statistical Approach for Real-time Robust Background Subtraction and Shadow Detection》作者源代码(The "src" folder contains all of the source code. To run the program, follow these simple steps: 1. Start MATLAB and ensure the "src" folder is your current working directory. 2. Edit "bs.m" and "classify.m" so that the file paths point to the proper directories as specified. 3. In the MATLAB environment type "bs" which will train the background model from the sequence you specified in (2). 4. In the MATLAB environment type "classify" which will classify the sequence of images you specified in (2). 5. Now the classified images should be saved to disk in the folder you specified in (2).)