glint

说明：  简单的数字图像处理程序，实现灰度化，二值化，边缘检测等(Simple digital image processing program, graying, binarization, edge detection, etc....)

MRF代码实现,visual C++ 代码，不错，可以尝试(an implementation of MRF)

图像分割经典算法GraphCut的实现代码，亲测可用。(An implementation of GraphCut Algorithm, which is a classical method in image segmentation field.)

超像素分割程序，既有原码，也有可执行程序，验证过，好用。(Super-pixel segmentation procedure, both the original code, there are executable programs, proven, easy to use.)

说明：  用VC实现数字减影算法，通过模板匹配，再对两幅图像相减，即用盈片中减去蒙片，从而实现突出血管区域的目的。【源码加文档说明】(Using VC to achieve digital subtraction algorithm, template matching, and then the subtraction of two images, that the film with surplus minus mask, in order to achieve the purpose of highlighting vascular region. 【Source】 plus documented)

平台基于visual studio2015，使用opencv函数实现双边滤波，进行图像处理(bilateral Filter based on opencv)

这个源代码是用来实现图形之间的基本运算的，包括求交集、并集、差集等等。而且图形的形状也可以任意选择，可以是圆、线段、点、多边形等等。(the source code is used to achieve the basic graphics operations, including for intersection and set difference, and so on. The shape and graphics can choose freely, it can be won, segment, points, polygons, and so on.)

该函数用来实现快速离散余弦变换。该函数利用2N点的快速付立叶变换来实现离散余弦变换(This function is used to implement fast discrete cosine transform. 2N points of the function using the fast Fourier transform to achieve the discrete cosine transform)

说明：  傅立叶变换在图像处理中的重要作用： (A) 图像增强与图像去噪 绝大部分噪音都是图像的高频分量，通过低通滤波器来滤除高频噪声；边缘也是图像的高频分量，可以通过添加高频分量来增强原始图像的边缘； (B) 图像分割与边缘检测 提取图像高频分量 (C) 图像特征提取 形状特征：傅里叶描述子 纹理特征：直接通过傅里叶系数来计算纹理特征 其他特征：将提取的特征值进行傅里叶变换来使特征具有平移、伸缩、旋转不变性 (D ) 图像压缩 可以直接通过傅里叶系数来压缩数据；常用的离散余弦变换是傅立叶变换的实变换； (Fourier transform in the important role of image processing: (A) image enhancement and image denoising Most of all images of high frequency noise by low pass filter to filter out high frequency noise edge is the image of the high frequency components can be enhanced by adding high frequency components to the edge of the original image (B) Image segmentation and edge detection High frequency components extracted image (C) image feature extraction Shape features: Fourier descriptors Texture: directly through the Fourier coefficients to calculate the texture features Other features: The characteristic value extracted by Fourier transform to the characteristics of translation, scaling, rotation invariance (D) image compression Fourier coefficients can be directly compressed data commonly used discrete cosine transform is the Fourier transform of the real transformation 朗读显示对应的拉丁字符的拼音)

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.)