改进RLS校正算法

数字水印参考代码，分别用checksum，lsb，patchwork等方式嵌入水印，并且附带计算信噪比和消除水印的代码(Digital watermark reference code checksum lsb in patchwork way embedded watermark and accompanying calculated signal-to-noise ratio and eliminate the watermark code)

使用 RANSAC 算法计算仿射变换矩阵(RANSAC algorithm using an affine transformation matrix)

说明：  人脸识别提出的LBP特征计算程序，简单实用的特征，可以得到统计的直方图特征(LBP features of face recognition proposed by the calculation procedure, simple and practical features of the histogram statistics can be characteristic of)

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)

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.)

将传统的串行均值滤波算法修改为基于CUDA的并行的滤波算法(Modify traditional serial mean filtering algorithm based on CUDA parallel filtering algorithm)

包含高光谱图像读取及格式转换，端元提取算法N-FINDR(Contains the hyperspectral image reading and format conversion, endmember extraction algorithm for N-FINDR)

最经典之做，保证别人没有上传过 实现文章 “GrabCut" Interactive Foreground Extraction using Iterated Graph Cuts 用graphcut实现图像分割，效果非常好(The most classic to do to ensure that other people do not realize uploaded article GrabCut Interactive Foreground Extraction using Iterated Graph Cuts with graphcut realize image segmentation, has very good results)

最小噪声分离变换（Minimum Noise Fraction Rotation，MNF Rotation）工具用于判定图像数据内在的维数（即波段数），分离数据中的噪声，减少随后处理中的计算需求量(Minimum Noise Fraction Rotation (MNF Rotation) tool is used to determine the intrinsic dimension (i.e. band number) of image data, separate the noise in data, and reduce the computational requirements in subsequent processing.)

说明：  基于标记的分水岭算法，弥补了传统分水岭算法存在的过分割问题。(Marker-based watershed algorithm makes up for the over-segmentation problem of traditional watershed algorithm.)