Contourlet变换的源代码，与广泛使用的空间图像处理

用vc++编程实现图像二值化，设定阈值为122即最大灰度的一半-Vc++ programming with image binarization, the threshold set for the 122 that is half the maximum gray

针对传统方法难以可靠估计图像中纹理单一区域像素点视差的问题,将纹理分析应用于立体匹配中,提 出图像分块整体匹配的方法。首先用LBP/C纹理分析方法对图像纹理进行描述 然后进行基于区域生长的扩张检 测,得到纹理单一图像块 最后对图像块进行整体匹配,得到纹理单一区域的稠密视差图。对国际标准图像进行测试, 结果表明该算法能提高纹理单一区域稠密视差图的精度,具有实用价值 -Due to the difficulty of getting disparity of less textured pixels with traditional approach, block matching algorithm with texture analysis was put forward. First, the images were described by LBP/C texture analysis. Then the expansion detection based on region growing was performed, and the less textured blocks were acquired. Finally the dense disparitymap of less textured area was obtained through block matching. The proposed algorithm was tested with the international standard image data and comparedwith some existing algorithms. The experimental results show that the proposed algorithm can improve the accuracy of disparitywhen handling less textured areas and can be used in practic

这是一个图像的预处理程序，把几个图像进行平均-This is an image preprocessing procedures, the average number of images

图象的边沿检测与提取，轮廓跟踪算法代码。边缘，轮廓提取-Image edge detection and extraction, contour tracing algorithm code. The edge contour extraction

图像反转源码，c代码，环境windows-source, c code, the environment windows!

em算法原理，帮助你理解EM算法，EM算法是 自然语言理解中的经典重要的算法，基本上是 学习自然语言理解的基础-EM algorithm, help you to understand the thereom of EM

计算机中表示图形、以及利用计算机进行图形的计算、处理和显示的相关原理与算法，构成了计算机图形学的主要研究内容-Said computer graphics, and the use of computer graphics calculations, processing and display the relevant principles and algorithms, constitute the main research content of computer graphics

基于kmeans的图像分割算法，首先得到图像，再确定分类，并计算各分类的均值，从而得到各个像素的分类。-Kmeans-based image segmentation algorithm, first of all get the image, and then determine the classification, and calculate the various categories mean, and thus obtain the classification of each pixel.

实现图像的中值滤波处理，从而实现对图像的处理-finish the process of median filtering

用于level set分割的matlab工具箱-For level set segmentation matlab toolbox