rgb2hsi

1.图像去噪MATLAB仿真程序.m 2.图像点扩展函数获取MATLAB仿真程序.m 3.约束最小二乘法图像复原MATLAB仿真程序.m(1.the simulation of denoise. 2.the method to get psf. 3.controlled least squre method to deblur image.)

弹流油膜数值计算画等高图，难以得到预想马蹄形特征，通过代码处理，可以方便的解决问题，得到满意的预想图(EHL film numerical draw contour map, it is difficult to obtain desired characteristic horseshoe, processing through the code, you can easily solve the problem, get a satisfactory RENDERING)

Kullback-Leibler Importance Estimation Procedure利用Matlab程序实现图像间KL散度的阈值分割(Kullback-Leibler Importance Estimation Procedure procedure using Matlab implementation KL divergence between the image of the threshold segmentation)

说明：  此代码是由FCM算法改变的且用于图像分割，比FCM算法对图像的分割的效果更好(This code is changed by FCM algorithm and is used for image segmentation, which is better than FCM algorithm for image segmentation)

应用DCT字典和KSVD学习字典，对图像进行简单的修复，可行性较高，速度不是很快。(Simple image restoration is feasible and not very fast.)

Jpeg2000静态库，只需Encoder和Decoder两个函数轻松搞定Jpeg2000和Bitmap的转换，带示范程序，非常有用(Jpeg2000 static libraries, Encoder and Decoder only two functions easy to get and Bitmap Jpeg2000 The change model procedures with very useful)

通过数字图像相关的方法计算两幅图像之间的位移，计算时间较长，是最基础的DIC，没有优化。(Digital image correlation method to calculate the displacement between the two images, the time is longer, is the most basic DIC, no optimization.)

php图像处理，用php实现，进行简单的操作，编辑，修改等功能(Intervention Image is a PHP image handling and manipulation library providing an easier and expressive way to create, edit, and compose images. The package includes ServiceProviders and Facades for easy Laravel integration.)

改进lee滤波源码，里面有im是原图 nim是噪声图像

一种基于半监督的svm的图像分类方法。该方法通过聚类核的方法利用无标记样本局部正则化训练核的表达式。这种方法通过图像直接学习一个自适应的核。该程序仿真的是文章：Semi-supervised Remote Sensing Image Classification with Cluster Kernels。大家可以参考下。(A semi-supervised SVM is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image, and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictionsds)