fangzhen

说明：  实现了图像的打开功能，并能实现图像打开时的扫描，渐进，马赛克等功能(To realize the image of the open function, and can achieve image scans open, progressive, mosaic and other functions)

CCD 摄像机内外部参数快速准确的标定方法(Fast and accurate calibration method for internal and external parameters of CCD camera)

图像检索，从600多张图片中检索出与目标图片相似度最高的。按照相似度顺序排列。(Image retri , retrieved more than 600 pictures in most similar to the target image. They are arranged in order of similarity.)

第8章 图象的检测及模板匹配 图象的分割与检测(识别)实际上是一项非常困难的工作。很难说清楚为什么图象应该分割成这样而不是那样。(Chapter 8 Detection of image template matching and image segmentation and detection (recognition) is actually a very difficult task. It is hard to say clearly why the image should be divided into such and not as.)

对于视频3D-DWT变换处理,嵌入水印图像。属于数字视频水印算法，包含水印嵌入算法以及水印提取算法。(3DDWT wavelet transform)

Impulse response, system response, for signal processing

自写M函数，做灰度图像的灰度级数及灰度范围的自定义设置。例如：将[0 255]的uint8图像变换成8级灰度的灰度范围为[0 7]图像或者[11.5 25.8]图像。 输出图像为double类，用户可将图像归一化后自行转换为所需类型。(This is a M function written by self, it can be used to rebuild a image with a given number of gray-level and a given gray-scale. Output image is double class.)

医学图像分割水平及方法理论书籍《Level Set Methods and Dynamic Implicit Surfaces》代码(Medical image segmentation level of theory and methodology of the book )

广度优先搜索和深度优先搜索在网络拓扑图上的实现。广度优先搜索是从某一节点开始，搜索与其线连接的所有节点，按照广度方向像外扩展，直到不重复遍历所有节点；深度优先搜索是从某一节点开始，沿着其搜索到的第一个节点不断深入下去，当无法再深入的时候，回溯节点，然后再在回溯中的某一节点开始沿另一个方向深度搜索，直到不重复的遍历所有节点。 (Breadth-first search and depth-first search in the network topology is realized. Breadth-first search is started from a node, searching all the nodes connected to its line, in accordance with the breadth direction as extracapsular extension, until no repeat traverse all nodes depth-first search is started from a node along its search to the first nodes deepening it, when it can not go any further, backtracking node, and then back again in the beginning of a node depth search in the other direction until the non-repetition of the traverse all nodes.)

用Matlab来实现PCA，并分别求出图像在第一、二、三主分量上的投影。(Using Matlab to implement PCA, and images were obtained in the first, second and third principal component on the projection.)