▍1. 基于matlab图像处理系统
说明： 图像处理MATLABGUI界面，实现对输入图像的超分辨率重建(image processing interface; boundary; limiting surface realize; achieve; bring about; come true rebuild; reconstruct; reestablish; rehabilitate)
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▍2. VTK+MFC
说明： 将VTK重建结果在MFC中显示，并有颜色与阀值设置。(VTK reconstruction results will be displayed in the MFC, and color threshold settings.)
▍3. Matlab-Image-Dehazing-Enhazing-master
说明： 该文件里含有多个图像增强算法，包含图像去雾，对比度增强，引导滤波，限制对比度自适应直方图均衡，直方图均衡等多种算法。(The file contains several image enhancement algorithms, including image defogging, contrast enhancement, guided filtering, contrast limiting, adaptive histogram equalization, histogram equalization and so on.)
▍4. 窗口界面使用KAYA SDK连接采集卡相机获取采集图像
说明： 窗口界面使用KAYA SDK连接采集卡相机获取采集图像(use KAYA sdk connect with grabber and capture image data)
▍5. Level.Set.Methods.And.Dynamic.Implicit.Surfaces
Level Set Methods and Dynamic Implicit Surfaces - Ronald Fedkiw(Level Set Methods and Dynamic Implicit Surfaces- Ronald Fedkiw)
▍10. GVF_Snake
GVF相关代码及相关论文资料()，含: GRADIENT VECTOR FLOW DEMONSTRATION(GVF) matlab code, ITERATIVE WATERSHED SEGMENTATION (c-code), 与SNAKE GUI代码。 (所含文件:gvf_v5.zip，MateiDemo.zip, snake_demo.zip) (gradient vector flow code and related information paper (), containing : GRADIENT VECTOR FLOW DEMONSTRATION (gradient vector flow) matl ab code, ITERATIVE WATERSHED SEGMENTATION (c-code). with Snake GUI code. (Contained in documents : gvf_v5.zip, MateiDemo.zip. snake_demo.zip))
▍11. 三次样条曲线拟和
三次样条曲线拟合类，可用于样条插值、拟合、预测等算法场合。(The Cubic Spline Interpolation class can be used for spline interpolation, fitting, prediction and other algorithms.)
▍12. WaveletsMultiwavelets
Fritz Keinert写的小波和多小波工具箱(Written by Fritz Keinert wavelet and multiwavelet Toolbox)
▍13. PCA
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.)
▍14. vtk-point-cloud-rendering
vtk显示点云，和点云三角网格化。 源代码已可运行，不过vtk的环境需要你自己配置(vtk display point clouds, and point cloud triangular grid. Source code has been run, but vtk environment requires you to configure)
▍16. epidemic1_big_screen-master(3)
说明： 通过已经获取的新冠肺炎数据 预测未来走势 并用网页的形式动态呈现(The novel coronavirus pneumonia data are used to predict the future trend and to dynamically display it in webpage form.)
▍17. mfile
说明： 批量提取遥感影像数据，以如何在一个文件批量读取geotif数据为例(Batch extraction of remote sensing image data)
▍18. GC-stereomatch
使用GC立体匹配算法生成视差图，内涵图片文件(GC disparity map)
▍19. ShearLab3Dv11
多尺度多方向性的剪切波Shearlet变换优于小波变换，里面包含很多例子，可以直接运行，可以用于图像去噪，分割，增强等，是一个优于小波的图像稀疏表示工具(Shearlet transform of multi-scale and multi-directional shear wave is better than wavelet transform. It contains many examples and can run directly. It can be used for image denoising, segmentation and enhancement. It is an image sparse representation tool better than wavelet transform.)
▍20. ShearLab3Dv11
说明： 多尺度多方向性的剪切波Shearlet变换优于小波变换，里面包含很多例子，可以直接运行，可以用于图像去噪，分割，增强等，是一个优于小波的图像稀疏表示工具(Shearlet transform of multi-scale and multi-directional shear wave is better than wavelet transform. It contains many examples and can run directly. It can be used for image denoising, segmentation and enhancement. It is an image sparse representation tool better than wavelet transform.)
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