readhdf

8通道GRAPPA并行重建算法，4倍加速(Parallel reconstruction algorithms ,GRAPPA，R=4)

图像处理均值漂移算法平滑处理meanshift(mean shift)

二维线性判别 功能比较强 二维线性判别 功能比较强(Img = imread( twoObj.bmp ) )

本人搜集的沙威老师关于CS所有的资料，包括代码，论文，评论等等，希望对大家有用。(Javert I have collected all of the teachers on the CS data, including code, papers, comments, etc., want to be useful.)

这个函数分配一个数据缓冲区与多个颜色指定系统上的乐队。这种类型的缓冲区允许表示彩色图像(例如,RGB)。 这个函数为每个指定分配缓冲区,一个二维表面颜色乐队。您可以使用MbufAlloc1d()和MbufAlloc2d()来创建单独的乐队一或二维 数据缓冲区,分别。 分配一个缓冲区后,我们建议您检查是否操作成功,使用MappGetError(),或通过验证,不是M_NULL返回的缓冲区的标识符。(This function allocates a data buffer with multiple color bands on the specified system. This type of buffer allows for the representation of color images (for example, RGB). This function allocates buffers that have a two-dimensional surface for each specified color band. You can use MbufAlloc1d() and MbufAlloc2d() to create single band one- or two-dimensional data buffers, respectively. After allocating a buffer, we recommend that you check if the operation was successful, using MappGetError(), or by verifying that the buffer identifier returned is not M_NULL.)

此程序为交互多模型的滤波器设计，采用了当前统计模型，跟踪效果比较理想(This program is interacting multiple model filter design, the current statistical model, the effect of tracking is ideal)

MRI 读入k空间数据调整中心并进行傅里叶变换显示图像(MRI k-space data is read into the center and adjust the display image Fourier transform)

基于遗传模拟退火和Otsu法的图像分割。采用一种基于模拟退火算法(SA)的混合遗传算法(GASA),来进行Otsu方法选择阈值，其中进行求解时是非线性的遗传算法（GA）的应用优化了求阈值过程，并尽可能地减少其运算量,而加入SA则避免了遗传算法(GA)常见的早熟收敛现象,从而实现有效简单的图像分割。 (adopt hybrid genetic algorithm(GASA) based on simulated annealing algorithm,choose threshold by Ostu method,which applicated the non-linear genetic algorithm(GA) allows us to optimize the process of threshold. And, where possible, to reduce the computation. in order to achieve effectivly and simply image segmentation. Combination SA is to avoid the common phenomenon about premature convergence in genetic algorithm (GA) to achieve a simple and effective image segmentation.)

用于SIFT变化的关键点判断，定对比度和herrian矩阵，最后结果为关键点在DOG里的坐标！(Change for the SIFT key points to determine, set contrast and herrian matrix, the final results for the key points in the coordinates in the DOG!)

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.)