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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)

说明：  结合模糊C均值聚类算法与水平集方法的图像分割代码，分割效果良好。(The image segmentation code based on fuzzy c-means clustering algorithm and level set method has a good segmentation effect.)

拉普拉斯变换的源代码，适合做图像处理及其他使用，有启发作用。(Laplace transform of the source code, suitable for image processing and other use, stimulating.)

DC图像转BMP源码，程序调用API函数把DC图像直接写入BMP图片中,不使用临时组件中转。(DC image transfer BMP source , the program calls API function to DC BMP picture image is written directly , without the use of temporary transit components .)

基于基元共生矩阵的纹理特征提取。通过5个基本的方格来检测图像并生成图像的基元共生矩阵，并从矩阵中提取其纹理特征信息。(Texton occurrence matrix based texture feature extraction)

book of image fusion

说明：  图像的尺度不变特征特征点提取，快速提取图像的特征点(SIFT feature extraction of image)

图片极坐标转换,可实现极坐标转换，以及求傅里叶变换(Picture polar coordinate conversion, convert polar coordinates can be realized, as well as seeking the Fourier transform)

说明：  用于图像畸变的校正，很实用好用，本人自己编写的(Correction for image distortion, very practical easy to use, I have written the)

图着色问题（Graph Coloring Problem, GCP）又称着色问题，是最著名的NP-完全问题之一。路线着色问题是图论中最著名的猜想之一。(Graph coloring problem (Graph Coloring Problem, GCP), also known as coloring problem, is the most famous NP-complete problems. Line graph coloring problem is one of the most famous conjecture.)