我的一个图像处理作业，实现了基本的图像处理功能，希望那个对你有用...

针对图像的灰度变换，阈值，直方图，线性灰度变化，灰度分布均衡化的程序。取自《vc++图像处理程序设计》第4章-For the image gray-scale transformation, threshold, histogram, linear gray scale, gray scale distribution of equalization process. Retrieved from " vc++ image processing program design," Chapter 4

基于高层语义的图像检索算法，文件为pdf文档，很好很新的资料。-High-level semantic-based image retrieval algorithm, a document for pdf documents, new information is very good.

主要实现数字图像的打开和傅立叶变换和反变换，现实变换结果-The main achievement of the opening of the digital image and Fourier transform and inverse transform, the reality transform results

对图像进行傅立叶变换处理（图像变换）的源代码，编译后的可执行文件-right image Fourier transform (image transformation) of the source code, the compiled executable file

关于数学计算――计算两点间距离 英文网站，对于简单地计算涉及多边形的运算实用性、理解性比较强-on mathematical calculations-- calculate the distance between two points English website, For simple calculations involving the polygon operations practical, understanding sexual stronger

本例主要是采用opencv进行的细胞个数的识别，效果较好-Opencv in this case is mainly used for the identification number of cells, the effect well

sift算法的c算法，基于opencv的，一个大牛写得，很厉害的。-c algorithms sift algorithm, based on the opencv, a large cattle write, it is powerful.

针对摄像机固定和共面约束条件下进行目标定位,提出了一种简单可行的全新算法。该算法避开了烦琐的摄像机标定这一过程,也不用精确地求解单应性矩阵。只是运用射影几何的性质,通过简单的几何关系,对非标定单摄像机拍摄的单幅图像,求解其从2D图像平面到真实的3D平面的非线性单映射关系。该算法为解决计算机视觉的测量、定位、三维重建等问题,提供一种全新的思路。 -against cameras fixed and coplanar binding conditions for target location, a simple new algorithm. The algorithm avoid the cumbersome process of the camera calibration, and it does not accurately be solved single matrix. Just use projective geometry of nature, by simple geometry, orders for non-standard video camera in a single image. Solving its two D images from two-dimensional to three real plane D nonlinear single map. The algorithm to solve the measurement of computer vision, positioning, three-dimensional reconstruction, with a brand new idea.

数字图像课程处理作品-Curriculum deal with digital image works

MATLAB 给图像添加各种噪声：如椒盐噪声，高斯噪声、乘性噪声等等。-MATLAB add all kinds of noise to the image: If salt and pepper noise, Gaussian noise, multiplicative noise and so on.