CS-based-on-FFT-or-DWT

遥感图像除云软件，原理是图像同时期替换掉有云区域，使用IDL语言编写(remove cloud from remote sensing image)

image processing for hand guesture

利用汉宁窗设计Ⅰ型数字带阻滤波器,通过Matlab实现。(Band Reject Digital Filter based on HanningI though Matlab.)

混合高斯模型的背景减除法和相邻帧差法相结合进行目标检测的程序，内附视频(The background of the gaussian mixture model reduction division and adjacent frame differential method for target detection with the program, enclosing video)

说明：  遥感高光谱图像处理，实现丰度估计；传统sansul算法(remote sensing,image processing,abundance estimation method)

用八叉树法对逆向工程得到扫描的三维实体模型图像处理，实现了对大量点云数据进行三维网格构建。(Octree method of reverse engineering can be scanned 3D solid model of image processing, realize the construct 3D mesh of a lot of point cloud data.)

Matlab程序，用于图像去噪声处理，特色是能够在去噪时保护图像边缘，是非线性滤波处理(Matlab program for the image to deal with noise, features that can protect the edge denoising is nonlinear filtering deal)

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

对理想的心音信号加入噪声，仿真成实际带噪声的心音信号，然后对其进行维纳滤波程序(The ideal heart sound signal added noise, simulation into actual heart sounds with noise signal, and then its Wiener filtering program)

基于MATLAB GUI的图像处理界面，包括基本的图像处理功能(Graphical interface construction based on image processing)