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说明：  通过利用“Otsu”方法对图像进行全局阈值分割处理。然后，将灰度图转化成二值图，为获得大豆颗粒计数和大小做准备。调用函数获得图像连通图的数量，并测量标注矩阵中每个标注区域的属性，获得每个标注区域的长度。最后通过寻找每个区域的重心数，即可统计出大豆的个数(The Otsu method is used to segment the image. Then, the gray-scale image is transformed into a binary image to prepare for the soybean particle count and size. Call the function to get the number of connected graphs, measure the attributes of each annotation region in the annotation matrix, and get the length of each annotation region. Finally, the number of soybean can be calculated by finding the number of barycenters in each region)

TIP10的paper "Image Deblurring and Super-Resolution by Adaptive Sparse Domain Selection and Adaptive Regularization" 的代码。一个图像去噪和超分辨的算法(TIP10' s paper " Image Deblurring and Super-Resolution by Adaptive Sparse Domain Selection and Adaptive Regularization" code. Image denoising and super-resolution algorithm)

本程序可以实现对图像的中值滤波，从而除去图像中的某些干扰(This procedure can be achieved on the image median filter, thereby removing some of the interference image)

把图像处理的MATALAB程序转化为C++程序(put image processing procedures into MATLAB C Program)

用matlab实现的基于广义S变换的图像去噪分型处理方法，简单易读(Using matlab realize the generalized S transform-based image denoising typing treatment methods, a simple easy-to-read)

DCT1实现一维离散余弦变换； DCT2实现二维离散余弦变换； 其中使用的算法是碟形算法来实现频域变换(DCT1 peacekeeping achieve a discrete cosine transform; DCT2 achieve two-dimensional discrete cosine transform; the use of the algorithm is dishing algorithm to achieve the transformation frequency domain)

改进的分水岭算法，利用基于重建的开闭算法，有效的解决了过分割问题，尤其适用与医疗血细胞的分割问题(Improved watershed algorithm, based on the reconstruction of the opening and closing algorithm, effectively resolved the issue of over-segmentation, in particular with the medical application of the division of blood cells)

s变换；广义s变换；高斯邻域；时频分析；滤波(s transformation generalized s transformation Gaussian neighborhood time-frequency analysis Filtering)

本程序给出一个利用高斯法近似求解病态方程的解的例子(This program gives a Gaussian approximation method for solving equations morbid examples)

用MATLAB实现不规则图像的面积测量，采用像素灰度值的占比进行实现(Area Measurement of Irregular Images Using MATLAB)