bianyuantiqu

利用核函数进行遥感图像的分类，本程序再支持向量机的基础上引入了核函数进行图像分类，是分类效果更加明显(Use of nuclear function remote sensing image classification, the program no longer support vector machine based on the introduction of the kernel function for image classification, classification effect is more pronounced)

说明：  分子图像处理的软件，但没有数据库，具体操作看操作说明(Molecular image processing software, but there is no database, see the specific operation instructions)

基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类，即把收敛到同一点的起始点归为一类，然后把这一类的标号赋给这些起始点，同时把包含像素点太少的类去掉。然后，采用阈值化分割的方法对图像进行二值化处理 (Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixels, that is, to converge to the same point as a starting point to the category and then assigned to this type of labeling of these starting points, at the same time to contain too few pixels to remove the category. Then, using thresholding segmentation method of binary image processing)

There is a BCB program for digital image to establish ground truth image which test the original image.

orl人脸库，40个人，每人10幅图像。(orl face database, 40 individuals, 10 images per person.)

快速鲁棒性Pca方法的一段matlab程序(fastrpca eneneneneen)

图像分割及二值化源码。该程序是交通标识识别的一部分。(Image segmentation and binary code. The traffic sign recognition program is part of.)

cvpr2012_oral On Multiple Foreground Cosegmentation(In this paper, we address a challenging image segmentation problem called multiple foreground cosegmentation (MFC), which concerns a realistic scenario in general Webuser photo sets where a finite number of K foregrounds of interest repeatedly occur over the entire photo set, but only an unknown subset of them is presented in each image. This contrasts the classical cosegmentation problem dealt with by most existing algorithms, which assume a much simpler but less realistic setting where the same set of foregrounds recurs in every image. We propose a novel optimization method for MFC, which makes no assumption on foreground configurations and does not suffer from the aforementioned limitation, while still leverages all the benefits of having co-occurring or (partially) recurring contents across images. Our method builds on an iterative scheme that alternates between a foreground modeling module and a region assignment module, both highly efficient and scalable. In part)

主要是对视网膜图像进行血管分割，效果还不错(Primarily on retinal vascular image segmentation, the effect was not bad)

说明：  基于各向异性扩散方程的一款经典的ＳＡＲ图像相干斑噪声抑制的算法实现，可以直接用的，效果很好！(Anisotropic diffusion equation based on a classic SAR image speckle noise reduction algorithm can be directly used, very good!)