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本人开发的火焰识别程序，包括otsu自适应阈值，canny边缘检测，形态学膨胀、腐蚀操作，尖角判别，圆形度计算。在vc下编译通过。(development of the flame identification procedures, including otsu adaptive threshold, canny edge detection, Morphological expansion, corrosion operation, pointed discriminant, circular calculation. Under the vc compile.)

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.)

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

实现图像的旋转，根据旋转矩阵进行旋转,并对结果进行调整(rotate picture)

Harris角点检测，关于角点的应用在图像处理上比较广泛，如图像匹配(FPM特征点匹配)、相机标定等。网上也有很多博客对Harris角点检测原理进行描述，但基本上只是描述了算法流程，而其中相关细节并未作出解释，这里我想对有些地方做出补充说明，正所谓知其然知其所以然，如有不对，还望指正。(Harris corner detection)

用opencv实现对一幅图像的小波变换 opencv 图像二维小波变换(The wavelet transform of an image with opencv)

医学图像处理：P0701：细胞边缘检测；702：癌细胞形态学分析；P0703：癌细胞颜色分析(Medical Image Processing: P0701: cell edge detection 702: morphological analysis of cancer cells P0703: color analysis of cancer cells)

说明：  特征检测与匹配的目标是识别一个图像中的关键点与另一个图像中的对应 点之间的配对。(The goal of feature detection and matching is to identify the key points in one image and the corresponding points in another image)

26个不同影像处理程序,以VC++开发,是了解影像入门好帮手(26 different image processing procedures to VC++ Development is helpful to understand the image entry)

说明：  使用tensorflow框架搭建神经网络，从单目图像中估计深度值(Using tensorflow framework to build a neural network to estimate depth from monocular images)