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实现图像的Contourlet变换，显示图像变换后每一层的图像。(Realize the Contourlet transform of the image , each layer of image is displayed after transform.)

说明：  《80例上手Delphi7编程_06图形图像多媒体》书附盘。包括镜框、渐变色、动画、艺术字等图像处理示例。("80 cases easily Delphi7 programming _06 imagery multimedia" book with CD. Including the frame, graded color, animation, art images, such as word processing examples.)

数字图像抠图源代码,是由一个外国人写的，非常好用，我希望能和大家一起分享(digital image matting matlab code written by a foreigner,it is very useful and I would like to share with everyone)

施法中新版《计算几何与计算机图形学》，书中所带光盘，包含书中源码和其团队开发的软件，能够实现曲线曲面拟合和编辑(The new cast of Computational Geometry and Computer Graphics , the book brought the disc that contains the source code in the book and his team developed software enables curve and surface fitting and edit)

针孔模型中单应矩阵的求解 mian函数，测试单应矩阵计算的算法，程序流程如下 1、 读入两个图像。 2、读入4组对应点。 3、调用CalcH函数计算H矩阵。 4、在第一幅图中用鼠标选择一点。 5、调用WarpH函数计算在第二幅图中的对应的。 6、显示结果.(Pinhole model for solving the homography mian functions, test homography computation algorithm, program flow is as follows 1, read the two images. 2, 4 reads the corresponding points. 3, call CalcH function to calculate the H matrix. 4, in the first picture using the mouse to select it. 5, call WarpH function calculation in the second picture in the corresponding. 6 displays the results. )

【实例简介】基于模板匹配的数字图片识别，使用opencv3进行图像处理

Mean shift algorithm for segmentation and smoothing images. the example images are horses.

一种基于特征点的图像匹配算法 一种基于特征点的图像匹配算法(Feature point based image matching algorithm based on feature points matching algorithm)

将图片进行8*8块的dct变换，以及8*8块的反变化恢复原图像(use 8*8 block dct to chang image, and use 8*8 block idct to renew image.)

本文主要介绍遗传算法的基本理论，叙述遗传算法在图像增强的的主要应用，即将原始图像变得更加清晰，特征变得更加明显。 现今关于图像增强的算法有很多，而这些算法大多是基于退化函数或者点扩展函数的知识进行图像处理的。当图像出现模糊或噪声影响大时，设计出的图像清晰化的效果肯定不够理想，因此有必要对图像进行增强处理。于是，可利用到遗传算法这种成熟稳定的仿生物进化的全局寻优算法，进行图像增强，由于遗传算法控制参数少、自适应度高，将选择该方法对图像退化分别进行不同的清晰化处理. 这样既增强了图像的对比度,又克服了传统直方图均衡化处理所造成的灰度级损失等缺点。 通过实验去表明，遗传算法从全局寻优的角度出发，能够较为精确地估计退化系统函数。和传统的线性增强、直方图均衡进行比较。实验结果表明该方法能改善原图像视觉效果，便于之后的图像分析。 (This paper mainly introduces the basic theory of genetic algorithm, genetic algorithm (ga) in the main application of image enhancement, the original image is more clear, characteristic becomes more obvious. Today about the image enhancement algorithm are many, and most of these algorithms is based on the degradation function or the knowledge of the point spread function of image processing. When the image appears fuzzy or noise influence, designed the image clarity of effect must not ideal, therefore it is necessary to enhance the image. Then, genetic algorithm is available to the mature and stable evolution of the global optimization algorithm, for image enhancement, due to less genetic algorithm control parameters, since the high fitness, will choose the method of image degradation, respectively, to manipulate the different motivation. It can enhance the image contrast, and overcome the traditional histogram equalization processing grayscale loss caused by the faults. Throug)