CT

python实现的三维空间维罗尼图算法演示。(3d voronoi use python)

color image watermarking with color

视频图像处理，采用背景减除法中混合高斯建模进行视频前景和背景的分离(Video image processing, background subtraction method using Gaussian mixture modeling to separate the foreground and background video)

影像仿射变换特征提取，结合 sift 等局部特征可以处理较大视角变化下的图像匹配。(This is an implementation of Hessian-Affine detector. )

类似PChunter的内核工具。本工具是应用层的源码。适合内核新手(Similar PChunter core tools. This tool is the source application layer. Suitable for novice kernel)

读取单幅envi图像格式的img图像，并将其显示出来(read img)

将原图像进行退化处理（选择大气湍流导致图像模糊时相应的PSF），然后将退化后的图像进行复原（使用维纳滤波、直接逆滤波）.(The original image degradation process,and then restore the degraded image with Wiener filtering and inverse filtering.)

利用非局部均值的算法对图像做去噪，速度比较快，但效果一般，存在一定局限性(Using non-local mean algorithm to denoise image is faster, but the effect is general and there are some limitations.)

说明：  通过利用“Otsu”方法对图像进行全局阈值分割处理。然后，将灰度图转化成二值图，为获得大豆颗粒计数和大小做准备。调用函数获得图像连通图的数量，并测量标注矩阵中每个标注区域的属性，获得每个标注区域的长度。最后通过寻找每个区域的重心数，即可统计出大豆的个数(The Otsu method is used to segment the image. Then, the gray-scale image is transformed into a binary image to prepare for the soybean particle count and size. Call the function to get the number of connected graphs, measure the attributes of each annotation region in the annotation matrix, and get the length of each annotation region. Finally, the number of soybean can be calculated by finding the number of barycenters in each region)

基于核函数的SAR图像目标识别,利用KPCA对SAR图像进行特征提取(SAR image target recognition based on kernel function，Use KPCA SAR image feature extraction)