EMDN

本程序集合了互信息配准，PV差值，powell算法，基于小波变换的图像融合的一整套算法。只需要在GUI界面输入两幅图像，即可自动完成图像的配准融合。程序包含Matlab源代码。用Matlab打开imagefusion.m，即会弹出gui界面。融合前要输入参考和浮动图像。图像要求像素的 长＊宽 一样。否则会报错。程序只能处理灰度图像，彩色图像也会转化成灰度图像处理。程序代码已经有详细的注释，方便读者理解。(The procedures set of mutual information, PV difference, powell algorithm, based on wavelet transform image fusion set of algorithms. Only need to enter the two images in the GUI interface, you can automatically complete the image registration fusion. Program contains Matlab source code. Using Matlab open imagefusion.m, gui interface will pop up. Fusion before the input reference and floating images. Image requires the same pixel length* width. Otherwise incorrect. Can only handle grayscale images, color images into gray image processing also. Program code has detailed notes, to facilitate understanding.)

基于光流场的交通汽车检测跟踪Traffic Vehicle Detection and Tracking Based on Optical Flow Field(Traffic Vehicle Detection and Tracking Based on Optical Flow Field)

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)

经典的数字图像处理的形态学处理，包含源代码(Digital image processing morphological processing)

通过高斯核密度估计计算多元变量之间的互信息熵(The mutual information entropy between multivariate variables is calculated by Gaussian kernel density estimation)

LBP（局部二值模式）特征提取，用于人脸识别，(LBP feature extraction for face recognition. . .)

本代码是基于MATLAB环境下的一种基于DWT的数字水印的嵌入与提取，本算法对各种噪声具有一定的抗鲁棒性。(The code is based on the MATLAB environment based DWT digital watermark embedding and extraction, the algorithm has certain anti robustness of various noise.)

matlab code for image fusion based on curvelet transform and genetic algorithm

一个光流算法的matlab源程序，在图像处理、前景检测与跟踪等方面有很多应用，推荐(An optical flow algorithm matlab source code in image processing, the prospects for detection and tracking, etc. There are many applications, the recommendation)

能够实现对SAR图像和其他类型的包含大量噪声的图像进行平滑去噪，在去除噪声的同时还能保持并增强边缘，适用于目标提取。(SAR images can be achieved and other types of containing large amount of noise in the image smoothing denoising, remove the noise while maintaining and enhancing the edge, suitable for object extraction.)