image_matching

读取图像，转化为二值，去除毛刺噪点像素，去除孤立的前景像素，膨胀，对颗粒进行计数(particle count，)

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.)

利用Hough变换检测抛物线的算法。利用标准Hough变换从二值（黑白）图像中检测抛物线。(The use of parabolic Hough transform detection algorithms. Standard Hough transform from the binary (black and white) image in the detection of a parabola.)

说明：  用水平集做的 MRI大脑图像分割 内有用法说明 （带图形界面）(To do with the level set within the MRI brain image segmentation instructions (with graphical interface))

遥感图像处理的基本操作：PCA变换、KT变换、直方图显示、彩色显示等(The basic operation of the remote sensing image processing: PCA transform, KT transform, histogram display, color display)

选择合适的样本特征点，然后可以将特征导入svm进行分类(After the image processing, the main information is obtained by PCA transform, and then the feature of texture information selection is put forward)

说明：  kl变换. KL变换的流程如下： （1)获取多幅图像的统计特性：图像之间的协方差 （2)获取协方差的特征值和特征向量，从而获取正交核:特征矩阵 （3)图像对应象素点对各个特征向量进行投影运算。(kl transformation)

Harris角点检测程序（内附示例图像），利用鼠标在图像上选择提取交点的区域，进行角点提取。程序语言简洁，利于初学者学习。(Harris corner detection procedures (with sample images), using the mouse in the image on the choice of extraction point of intersection of the region, for Corner Detection. Programming language is simple and conducive to learning for beginners.)

说明：  针对一维最大类间方差算法(1-Otsu)抗噪性能较低、二维最大类间方差算法(2-Otsu)计算复杂度高、实时性差的问题,提出一种基于改进的萤火虫算法(FA)优化二维Otsu图像分割算法(FA-2-Otsu).(In order to solve the problems of low anti noise performance of 1-otsu, high computational complexity and poor real-time performance of 2-otsu, an improved firefly algorithm (FA) is proposed to optimize the 2-otsu image segmentation algorithm (fa-2-otsu).)

对比度拉伸，对原始图像进行对比度拉伸，从而得到拉伸后的图像(tensile contrast, the original image contrast stretching, and thus drawing the images)