uuity7i

输入一个带权无向图的顶点数、边数、各条边信息（两个顶点和权值），建立该图的邻接矩阵结构，输出该邻接矩阵。将上述无向图邻接矩阵转换为邻接表结构，输出该邻接表；根据该邻接表对无向图进行深度优先遍历序列和广度优先遍历序列，并输出遍历结果；用prim算法实现构造该带权无向图的最小生成树，并将该最小生成树的各条边信息输出。(Enter a weighted undirected graph with vertices, edges, each of the side information (two vertices and weights), the establishment of the adjacency matrix structure, the output of the adjacency matrix. The above undirected graph adjacency matrix into adjacency list structure, the output of the adjacency list according to the adjacency table undirected graph depth-first traversal sequence and breadth-first traversal sequence, and outputs through the results using prim algorithm construct the weighted undirected graph minimum spanning tree, and the minimum spanning tree information on respective sides of the output.)

基于小波变换的使用SPIHT算法进行图像压缩，并对原有的算法进行优化(Based on wavelet transform using the SPIHT algorithm for image compression, and the original algorithm to optimize)

利用k—mean算法根据U、V进行聚类分块，最后完成图像分割，分割出得块用不同的灰度等级表示出来。(K-mean algorithm to cluster sub-blocks according to the U, V, to finalize the image segmentation, segmentation have blocks with different gray levels represented.)

人民邮电出版社，《VC++数字图像处理典型算法及实现》-- 第9章图像分割。 包括图像的并行边界分割、串行边界分割、并行区域分割、串行区域分割、Canny算子的实现等源代码(Posts )

图像分割处理的小波变换算法源代码，使用vc++(Wavelet transform image segmentation algorithm source code vc++)

包括图像输入（打开文件、采集、捕捉图像、从剪贴板粘贴、打开扫描软件、灰度化、添加随机噪声、椒盐噪声、去噪声）、图像处理（几何变换、灰度反转、直方图均衡化、直方图统计、图像复原、边缘提取、伪彩色、二值化、图像变换）、图像输出（另存图像、打印输出、复制到剪贴板）(Including image input (open the file, capture, capture images, paste from the clipboard, open the scanning software, graying, adding random noise, Salt and pepper noise, to noise), image processing (geometric transformation, gray inversion, histogram equalization oriented, histogram statistics, image restoration, edge extraction, pseudo-color, binary, image transform), image output (save the image, print out, copy to clipboard))

Visual C++数字图像实用工程案例光盘代码(Visual C++ Digital image utility works case CD-ROM code)

这个函数分配一个数据缓冲区与多个颜色指定系统上的乐队。这种类型的缓冲区允许表示彩色图像(例如,RGB)。 这个函数为每个指定分配缓冲区,一个二维表面颜色乐队。您可以使用MbufAlloc1d()和MbufAlloc2d()来创建单独的乐队一或二维 数据缓冲区,分别。 分配一个缓冲区后,我们建议您检查是否操作成功,使用MappGetError(),或通过验证,不是M_NULL返回的缓冲区的标识符。(This function allocates a data buffer with multiple color bands on the specified system. This type of buffer allows for the representation of color images (for example, RGB). This function allocates buffers that have a two-dimensional surface for each specified color band. You can use MbufAlloc1d() and MbufAlloc2d() to create single band one- or two-dimensional data buffers, respectively. After allocating a buffer, we recommend that you check if the operation was successful, using MappGetError(), or by verifying that the buffer identifier returned is not M_NULL.)

本程序为图像锐化的经典程序，源码里有详细的标注。(the procedures for sharpening images of the classic procedures are detailed source of tagging.)

基于边缘特征的图像配准算法源码 基于边缘特征的图像配准算法是将不同时间、不同的传感器（成像设备）或不同条件下（天候、照度、摄像位置和角度等）获取的同一场景的两幅或多幅图像根据其边缘特征进行匹配、叠加的处理，最终生成一幅全景图像的方法。该方法具有抗噪性强，匹配速度快，误匹配率低，适用于多种类型的图像等优点，主要可以运用于以下领域： （1）军事研究领域，如飞行器辅助导航系绞、武器投射系统的末制导以及寻地等应用研究； （2）医学图像分析，如数字剪影血管造影DSA血管造影术、肿瘤检测、白内障检测、CT、MRI、 PET、 SPECT图像结构信息融合； （3）模式识别，如特征识别、波形分析、签名证实、目标物运动跟踪、序列图像分析等； （4）计算机视觉，可用于目标定位、自动质量控制等； （5）遥感数据分析，多电磁波段图像信息融合，如多谱段的等场景分类、定位和识别定义好的或已知特征的场景、自然资源监控、核生长监控、市区增长检测等。 本算法实现使用VC++6.0为开发环境，目前只支持灰度图像，感兴趣的朋友可以进一步扩展。(Image registration is a fundamental problem in image processing, which is a process to match two or more images of the same scene taken at different times, from different viewpoints, or by different sensors. Image registration is an important technique for a great variety of applications such as medical image analysis, computer vision, remote image data analysis, image information fusion, and the recovery of the 3–D characteristics of a scene.)