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说明：  基于ESS303开发板的OV7670_VGA拍照功能实现(Implementation of OV7670_VGA camera function based on ESS303 development board)

文字可视化，对于给定的文本，输出可视化效果的程序。(word visualization)

基于matlab的三维重建代码，提取两幅图片的匹配点(Based on three-dimensional reconstruction of the matlab code, extract the two images match point)

图像质量评价中全参考方法IWSSIM的代码，是经典方法SSIM的升级(The code of IWSSIM, a full reference method in image quality evaluation, is an upgrade of SSIM, a classical method)

主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间。给定 n 个变量的 m 个观察值，形成一个 n ′ m 的数据矩阵， n 通常比较大。对于一个由多个变量描述的复杂事物，人们难以认识，那么是否可以抓住事物主要方面进行重点分析呢？如果事物的主要方面刚好体现在几个主要变量上，我们只需要将这几个变量分离出来，进行详细分析。但是，在一般情况下，并不能直接找出这样的关键变量。这时我们可以用原有变量的线性组合来表示事物的主要方面， PCA 就是这样一种分析方法。(Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical method to grasp the principal contradiction of things, it can be resolved diverse things out the main factors, revealing the essence of things, simplifying complex problems. The purpose of calculating the main component of high-dimensional data is projected to a lower dimensional space. Given n variables of m observations, forming an n ' m of the data matrix, n is usually large. For a complex matters described by several variables, it is difficult to know, so if you can grab something to focus on key aspects of analysis? If the main aspects of things just reflected on several key variables, we only need to separate out these few variables, for detailed analysis. However, in general, does not directly identify this critical variables. Then we can represent the major aspects of things with a linear combination of the original variables, PCA is one such analysis.)

说明：  matlab生成的源码，适合图像处理人员研究及其应用。不明白之处可一起讨论(matlab source code production chain)

说明：  用于Inkscape扩展gcode文件使用(Use for Inkscape extended gcode file)

说明：  Matlab实现简单图形处理，包括灰度、亮度、对比度变化等功能(Implement Simple Graphics Processing with matlab. Equipped with the function of gray level,brighteness and contrast ratio transfotmation.)

AForgeNet 是基于.net框架使用C#高级面向对象语言设计开发的专门为开发者和研究者学习和使用的开源图像处理类库，包括计算机视觉与人工智能，图像处理，神经网络，遗传算法，机器学习(AForgeNet is an open source image processing class library designed and developed for developers and researchers based on. net framework using C # advanced object-oriented language. It includes computer vision and artificial intelligence, image processing, neural network, genetic algorithm and machine learning.)

用于在图像处理以及计算机视觉中，作为测试的COIL20数据集(The COIL20 data set used as a test in image processing and computer vision)