demo

对于二值图像进行labeling,求的对象个数，每个对象的像素数，中心点，长宽高矮值等(labeling for bianry image)

图像增强的算法，但是有一定的局限性……但是对于一般比较典型的问题效果还是不错的……(Image enhancement algorithms, but there are some limitations ... but for a typical effect is good ...)

能够计算傅里叶描述子，并对图像进行重构，实现对目标图像和源图像的辨认(Fourier descriptors can be calculated, and the image reconstruction, image and the source image to target identification)

图像拼接源码实现，包括多频率图像融合，sift特征点配准算法(Image Stitching source implementation, including multi-frequency image fusion, sift feature points matching algorithm)

说明：  RM的编码过加性高斯白噪声信道（AWGN）后译码的C++ 实现程序，C语言产生高斯白噪声(RM of coded additive white Gaussian noise channel (AWGN) after decoding in C++ program, C language generated Gaussian white noise)

对图像进行镜像处理，是最基本的图像处理操作(Mirror image is the most basic image processing operations )

打开BMP图像 IHS Brovey图像融合(Open the BMP image IHS Brovey Image Fusion)

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)

说明：  讲述PS技术的抠图经典问题，帮助你快速熟悉抠图的精华！(PS about the classic problem of technology, matting, matting to help you quickly familiar with the essence!)

用Visual C++实现基于数学形态学的数字图像处理,包括二值图像的腐蚀,膨胀,开,闭,细化及中轴变换等运算.(Visual C++ using mathematical morphology-based digital image processing, including binary image erosion and dilation, opening, closing, thinning, and the central axis transform operations.)