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基于分块的人脸图像超分辨率学习算法实验平台，利用学习到的训练集图像信息对低分辨率图像超分辨率，并可以查看超分辨率后的图像块匹配结果（用鼠标双击结果显示窗口中的实验图像），可以设置实验参数。(Block-based face image super-resolution algorithm for the experimental platform to learn, learning to use the training set of low-resolution image information super-resolution images and can view the image super-resolution block-matching results (double-click with the mouse results display window of the experimental images), the experimental parameters can be set.)

说明：  数学形态学对信号进行去噪，效果较好，信号扰动特征得到很好保留(Mathematical morphology to signal de-noising effect is better to be a good signal to retain the characteristics of disturbance)

根据CT成像原理得到Sinogram图像，再经过Randon变换以及反向投影算法对物体图线进行复原。(It is a Matlab ToolBox which can solve CT problems or image reconstruction easily and convincely.)

FDK算法 重建三维图像，期中有GPU并行计算加速fdk算法的实例(back-projection to RECONSTRUCT 3D IMAGE)

本书介绍了图像去模糊化的一些基本的知识，并且主要针对svd和spectral decomposition的去模糊算法进行了介绍，以及对于这些方法的一些提高计算速度的算法进行了详细是介绍(This ebook intruduces some basic knowledge of deblurring, especially the methods of SVD and Spectral Decomposition, and some fast algorithms for the two methods.)

matlab光学仿真，模拟光线的反射、折射；非常强大的光学仿真软件。(Matlab optical simulation,Simulate the reflection and refraction of light;;very powerful optical simulation software.)

利用核函数进行遥感图像的分类，本程序再支持向量机的基础上引入了核函数进行图像分类，是分类效果更加明显(Use of nuclear function remote sensing image classification, the program no longer support vector machine based on the introduction of the kernel function for image classification, classification effect is more pronounced)

鼠标写毛笔字源码例程，程序结合易语言扩展界面支持库和图像格式转换支持库，实现用鼠标写出毛笔字的效果。可以展现多种毛笔字形态，启动时有使用帮助说明。(Mouse calligraphy source routines, programs combined with easy language support library expansion interface and image format conversion support library , use the mouse to write calligraphy achieve results. )

说明：  对图像进行行列循环加密，采用的是3维混沌系统来增强图像加密的安全性(The 3-D chaotic system is used to enhance the security of image encryption)

26个不同影像处理程序,以VC++开发,是了解影像入门好帮手(26 different image processing procedures to VC++ Development is helpful to understand the image entry)