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多种图像处理基本方法的源代码，包括图像分割和边缘检测，非常适合初学者参考使用。(A variety of basic methods of image processing source code, including image segmentation and edge detection, is suitable for beginners reference.)

vc++图像开发的附书光盘,包括众多的实例程序,每个程序都可以是功能完备的工具软件.(visual c++ image develop source code and instances)

这是基于图像处理，用MATLAB编程，对指定的图像进行缺陷检测和边缘提取的程序(This is based on image processing, using MATLAB programming, the images on the specified defect detection and edge extraction procedures)

数字识别PCA方法，对其它图像同样适用，程序简便。(Digital identification PCA method, on the other images of the same application, the program is simple.)

Labwindows/CVI实现了常见的数字图形处理算法，如滤镜，正交表换 边缘检测等(Common digital graphics processing algorithms, such as filters, orthogonal change of edge detection)

matlab写的对图像进行简单的伽马校正，代码中给出了两个例子(matlab write simple image gamma correction, the code gives the two examples)

对图像进行模糊处理，用逆滤波和维纳滤波恢复图像，也是实验时自己编写的代码，请多指教。(Fuzzy image processing, inverse filtering and Wiener filter to restore the image, but also experiments have written code, like him Zhijiao.)

对采集到的干涉条纹进行二值化，形态学细化等基本处理(The collected interference fringes binarization, thinning and other basic morphological processing)

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)

图像的各向异性扩散，利用matlab实现Perona_Malik算法，梯度阈值K通过对图像求解2-范数的方法迭代获得(Anisotropic diffusion images, using matlab to achieve Perona_Malik algorithm, the gradient threshold images by solving the K 2- norm method will be obtained)