matlab-eyes--detected-code

压缩文件中的代码可以读取图片并计算绿色植被的归一化植被指数，直接在IDL中打开即可使用(The code in the compressed file can read pictures and calculate the normalized vegetation index of green vegetation,and you can open it directly in IDL and use it.)

利用CSplitterWnd类实现对单文档工程进行视图区域的分割(Using the CSplitterWnd class implements the single document engineering for segmenting the view area)

说明：  基于各种算法的运动视频背景消除。使用opencv工具库，通过读取视频文件，处理视频，最后存储。(Background Subtract Algorithm)

高光谱图像MNF算法，实现高光谱图像的去噪，注释详尽(Hyperspectral image MNF algorithm to achieve denoising hyperspectral images, detailed comments)

说明：  可对lytro相机所得到的光场图像进行各种处理(The light field image obtained by lytro camera can be processed in various ways.)

梯度下降法的图形表示，里面有详细的中文注释，运行即可看到结果。(Gradient descent graphical representation, which the Chinese have detailed notes, you can see the results running.)

一种图像配准算法源码，实现了图像的配准拼接，看看就知道好。(A source image registration algorithm to realize image registration splicing to see will know better.)

说明：  基于最小二乘法的仿射变换 matlab实现(Least square method based on the realization of affine transformation matlab)

运动估计的几种方法，包括线性预测法、混合高斯法、特征值法和相邻帧差法等(Several motion estimation methods, including linear prediction method, mixed-Gaussian law, Eigenvalue and adjacent frames, such as poor law)

这是一个MATLAB工具箱包括32个降维程序，主要包括 pca,lda,MDS等十几个程序包，对于图像处理非常具有参考价值！！( ，This Matlab toolbox implements 32 techniques for dimensionality reduction. These techniques are all available through the COMPUTE_MAPPING function or trhough the GUI. The following techniques are available: - Principal Component Analysis ( PCA ) - Linear Discriminant Analysis ( LDA ) - Multidimensional scaling ( MDS ) - Probabilistic PCA ( ProbPCA ) - Factor analysis ( FactorAnalysis ) - Sammon mapping ( Sammon ) - Isomap ( Isomap ) - Landmark Isomap ( LandmarkIsomap ) - Locally Linear Embedding ( LLE ) - Laplacian Eigenmaps ( Laplacian ) - Hessian LLE ( HessianLLE ) - Local Tangent Space Alignment ( LTSA ) - Diffusion maps ( DiffusionMaps ) - Kernel PCA ( KernelPCA ) - Generalized Discriminant Analysis ( KernelLDA ) )