lapulsi

用visual c++编写的飞机飞行模拟航迹，其中包括VC源代码和模拟飞行图。(Written with visual c++ simulation of aircraft flight tracks, including the VC source code and simulation of flight plans.)

滤波器图像增强的matlab算法实现程序。本人自己给出的程序代码(gabor wavelet matlab algorithm. Program code given by the original author)

实现手机拍摄图像的二维码图像的提取，包括QR码的旋转与校正，也可以用于其他条码，但是效果不是很好(The realization of mobile dimensional code image captured image extraction, rotation and including a QR code correction can also be used for other bar code, but the effect is not very good)

用matlab开发的计算给定曲面点云的，高斯和平均曲率图(Matlab calculation developed by a given surface point cloud, the Gaussian and mean curvature map)

graphcut的最新改进，在网格上应用graphcut，作者将其称为gridCut,此压缩包内含文章与源代码，出自CVPR2012,关注计算机视觉的同学可以详细参考，代码已调试通过(the new advance of graphcut, named gridCut, derived from CVPR 2012, useful to guys on ComputerVision.The code is runnable.)

自己编写的关于2013年的文章 a variational method for multi-source remote-sensing image fusion 的程序，基本实现了相关功能。(I have written a progrma about a variational method for multi-source remote-sensing image fusion publish in 2013,and the basic functions of the problems have been solved.)

说明：  基于matlab平台的fft加窗插值算法，适用于信号分析(Wft window interpolation algorithm based on matlab platform, suitable for signal analysis)

本文针对多光谱图像配准中不同光谱图像间存在较大的灰度差异、同一景 物在不同波段表现的特征也各不相同等问题，提出了基于互信息相似性测度的 多光谱图像配准算法。(In this paper, multi-spectral image registration between images in different spectral gray there is a big difference, the same scene in different performance characteristics of band varies and so on, based on mutual information similarity measure for multi-spectral image registration algorithm .)

本案例是对人体医学断层切片的三维重建。这里的医学断层切片使用的是CT，重建的是人体躯干。(Three dimensional reconstruction of sectional slices of human medicine)

在统计学中，皮尔逊积矩相关系数（英语：Pearson product-moment correlation coefficient，又称作 PPMCC或PCCs[1], 文章中常用r或Pearson s r表示）用于度量两个变量X和Y之间的相关（线性相关），其值介于-1与1之间。在自然科学领域中，该系数广泛用于度量两个变量之间的相关程度。它是由卡尔·皮尔逊从弗朗西斯·高尔顿在19世纪80年代提出的一个相似却又稍有不同的想法演变而来的。这个相关系数也称作“皮尔森相关系数r”。(In statistics, Pearson product-moment correlation coefficient (English: Pearson product-moment correlation coefficient, also known PPMCC or PCCs [1], the article used or Pearson s r r representation) is a measure of the two variables X and Y between correlation (linear correlation), a value between-1 and 1. In the natural sciences, the coefficient is widely used to measure the degree of correlation between the two variables. It is made a similar Karl Pearson Francis Galton in the 1880s but made a slightly different idea evolved. The correlation coefficient is also called Pearson s correlation coefficient r .)