emd对一维信号去噪

说明：  用matlab实现的LSB的信息隐藏，有实验用的的图，可以完美运行(The information hiding of LSB realized by MATLAB, with experimental graph, can run perfectly)

说明：  本例程可以通过肤色进行人脸检测，同时包含一些对图像的基本处理方法，并集成了人脸识别的GUI界面。(This routine can detect face by skin color, and also includes some basic processing methods for image, and integrates GUI interface of face recognition.)

本程序为二值图像的处理。通过一种称为CNED(connectivity number based edge detection)的方法对二值图像进行边缘提取。结果表明这种方法比candy sober 等算子更加精确，效果更好。(This procedure for binary image processing. Through a known CNED (connectivity number based edge detection) method for binary image edge extraction. The results show that this method, such as candy sober than the operator more precise, better.)

主要功能是实现相机标定，以及实现反投误差，实现特征点的提前。(The main function is to achieve camera calibration and error to achieve the anti-investment, to achieve the feature points in advance.)

实现摄影测量中空间后方交会的问题，用以求得像片的内外方位元素(To achieve space resection in photogrammetry issues photograph to obtain the internal and external orientation elements)

本程序用于计算图像相似性,计算图像的7个不变矩，包含图像、源程序、网上的说明(3D_Moment_Invariant)

一种基于小波的图像分块处理并且水印嵌入和提取，适合初学者学习使用(Based on wavelet image processing block and the watermark embedding and extraction, suitable for beginners learning to use)

代码实现多目标粒子群算法，多目标粒子群算法是基于parato原则进行的目标优化实现的算法。而此文件就是多此算法的代码MATLAB的一种实现(Multiobjective particle swarm optimization (PSO) algorithm)

模糊聚类程序，并且有文档，详细的给出了模糊聚类算法的各个步骤。(Fuzzy clustering procedure, and there are documents, is given in detail the various steps in fuzzy clustering algorithm.)

基于采集的脑电导联信号，用matlab去噪和伪迹，最后绘制脑地形图。 去噪文件夹： FastICA_25文件夹为 fastICA函数；pca为pca 函数； av_sub伪迹减法去噪； ica_step1，ica_step2&pca 为ica与pca的去噪程序； wave_entro为小波熵的计算程序； topoplot为地形图函数； topo为画地形图程序；eloc32,eloc16为函数调用32导/16导的头皮电极分布位置 get_txt将采集的脑电数据转化为文本格式； readdata为依次读取文件夹中的一系列txt文件。(Based on the collection of brain conductivity signal, denoising using matlab, and pseudo-tracks, the final topographic map of brain mapping. Denoising folder: FastICA_25 folder function for FastICA pca function for PCA av_sub pseudo-trace subtraction de-noising ica_step1, ica_step2 )