on mathematical calculations

基于混合高斯的背景建模与阴影抑制算法研究,背景建模，目标检测-Based on Gaussian mixture background modeling and shadow suppression algorithm, background modeling, target detection

利用matlab对图象进行二维离散变换(Mallat快速算法)-using Matlab for discrete two-dimensional image transform (Mallat fast algorithm)

k-均值聚类法用于各种图像的聚类、分割问题，希望可以对您有利-k-means clustering method for a variety of image clustering, segmentation

功能描述：该程序给图像处理的平台，实现了图像处理的大部分算法，包括图像变换、图像处理和图像分析，功能丰富，参考性很强。 开发环境：C++ Builder 6.0 所用控件：Sunisoft SuiPack、SDL Component -Functional Description: The program for image processing platform, to achieve the majority of image processing algorithms, including image conversion, image processing and image analysis, feature-rich, highly reference. Development Environment: C++ Builder 6.0 used in the control: Sunisoft SuiPack, SDL Component

一个简单实现图片格式转换的工具,具体支持bmp,jpg,gig和tiff之间的互相转换,并附带浏览功能-Realize a simple picture format conversion tools, specific support for bmp, jpg, gig and the tiff between the conversion and incidental browsing

（1）应用9×9的窗口对上述图象进行随机抽样，共抽样200块子图象； （2）将所有子图象按列相接变成一个81维的行向量； （3）对所有200个行向量进行KL变换，求出其对应的协方差矩阵的特征向量和特征值，按降序排列特征值以及所对应的特征向量； （4）选择前40个最大特征值所对应的特征向量作为主元，将原图象块向这40个特征向量上投影，所获得的投影系数就是这个子块的特征向量。 （5）求出所有子块的特征向量。 -(1) the application of 9 × 9 window of these images at random, a total sample of 200 sub-image (2) all sub-images according to out-phase into a 81-dimensional row vector (3) all 200 lines for KL transform vector, derived its corresponding covariance matrix of eigenvectors and eigenvalues, in descending order by eigenvalue and the corresponding eigenvector (4) a choice to 40 corresponding to the largest eigenvalue eigenvector as the PCA, the original image block to the 40 feature vectors on the projection, the projection coefficients obtained by this sub-block eigenvector. (5) calculated for all sub-block eigenvector.

图像融合PixelFusion,也许会有些用处-This is a PixelFusion programe

首先介绍模糊集基本知识 其次K均值聚类算法(HCM)介绍 最后重点介绍了模糊C均值聚类， 模糊聚类是一种很重要思想，最近再图像处理中就用的了这种思想，也算是一点思维创新-First of all, introduce basic knowledge of fuzzy sets was followed by K-means clustering algorithm (HCM) focuses on the introduction Finally fuzzy C-means clustering, fuzzy clustering is a very important thinking, recently re-image processing on the use of such thinking, but also Innovative thinking is that

matlab图像融合工具箱,实现多源传感器图像融合功能-Matlab toolbox image fusion, multi-sensor image fusion function

实现对图象的特殊处理，主要是曝光的处理。里面包括测试图像。-realization of the special image processing, the exposure is the main treatment. Includes test images.