Can explain the image DCT transform process is small, but it is original

该源码是spiht多集树集合编码算法的图像编码，-The source tree is a collection of episodes SPIHT coding algorithm image coding,

用c++编写的基于内容的图像检索源代码。-With c++ Prepared content-based image retrieval source code.

图像处理源程序代码，关于图像的梯度锐化处理。-Image processing source code, the gradient sharpening on the image treatment.

没有经过改进的分水岭算法程序，可以根据具体问题对算法进行改进-Without going through improved watershed algorithm process, specific issues can be improved algorithm

关于程序的运行， DImageProcess工程只需载入Bmp格式的文件，便可通过菜单实现各种处理算法， 需要强调一点，其只对256色格式的图片进行处理。-on the process of operation, DImageProcess Bmp, only printed in the format of the document, menu can be achieved through various processing algorithms, the need to stress that their only pair of 256-color format photo processing.

一个优化了的H.264编码JM，在VC下能够顺利通过测试-Workspaces for MS Visual C++ 2003/2005 are provided with the names jm_vc7.sln - MS Visual C++ 2003 jm_vc8.sln - MS Visual C++ 2005

硕士论文：文本挖掘在Web日志数据预处理中的应用研究-Master s thesis: Text Mining in Web Log Data Preprocessing in the Applied Research

LensPhoto，世界领先的数字近景摄影测量系统软件2007版，绝对值得收藏。-LensPhoto, the world" s leading digital close-range photogrammetry system software, 2007 edition, is absolutely worthy of collection.

在计算机视觉中首先一步是计算每个摄像机的参数(外参和内参)，这是重建物体所必须的，这一个过程称为摄像机定标(camera calibration)。这是我自己写的一个简单的采用3维模板(模板是由黑白相间的格子组成，格子大小30cm×30cm，模板必须是三维，否则矩阵奇异)定标的程序，交互性比较好，每个角点通过鼠标点击自动获取。-Computer Vision in the first step is to calculate the parameters of each camera (outside the Senate and internal), which is necessary for the reconstruction of objects, which a process known as camera calibration (camera calibration). This is what I wrote it myself using a simple 3-dimensional template (template is composed of black-and-white lattice, lattice size of 30cm ?30cm, the template must be three-dimensional, or matrix singular) calibration procedures, better interactivity, each Corner automatic access through mouse clicks.

BlurTemplate.m为模糊模板函数子程序 DIPexp2.m为用逆滤波和维纳滤波进行恢复的源程序-Template function for the fuzzy BlurTemplate.m Subroutine DIPexp2.m using inverse filtering and Wiener filtering for the restoration of the source