geomosaic

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.)

基于双目的深度图获取,根据图像合成深度图左右视点( depth map based on binocular)

符合高斯分布的关于随机粗糙表面的生成代码(Meet the Gaussian distribution of the random rough surface on the generated code)

通过使用块匹配法实现运动矢量的检测，块大小和搜索区域大小可自定(Achieved through the use of block matching motion vector detection, block size and search area size can be customized)

对于离焦图像进行自动对焦的图像判定，通过对一些列的图像，从离焦到对焦再到离焦进行图像分析从而获得对焦图像的图片。(For the defocus image autofocus image determination, through a series of images into focus and then from defocus defocused image analysis to obtain a focused image of the picture.)

视频水印的matlab源码，文件较多，分为六个压缩包，如果您作相关方向的研究，可用作参考(Video Watermarking Matlab source, the paper more, divided into six compressed, If you made related to the direction of research, can be used as a reference)

bm4d图像去噪算法，可有效地去除图片中的噪点。(Bm4d image denoising algorithm, can effectively remove the noise in the picture.)

四种图像去噪程序，给原图像分别加上高斯噪声，椒盐噪声，乘性噪声，脉冲噪声后进行去噪，输出去噪后的图像(Four image denoising procedures, to the original image plus Gaussian noise, salt and pepper noise, multiplicative noise, impulse noise the Denoising output denoised image)

基于颜色的图像检索，将RGB转化成ＨＳＶ的方法(Color-based image retrieval, the method of RGB into HSV)

用MATLAN实现了FLL（锁频环）的热噪声误差、动态应力误差、总的跟踪误差与带宽、预检积分时间等的关系图(MATLAN achieve FLL (frequency-locked loop) thermal noise error and dynamic stress error, the total tracking error and bandwidth, preflight integration time diagram)