KL-face-recognition

说明：  区域生长算法。不用手动选择种子点，可自动选择。(Image segmentation by growing region method. No manual selection of seed points, automatic selection)

基于图像对比度和波段相关性的波段选择算法，适用于高光谱图像的特征选择(Bands selection algorithm based on image contrast and correlation of bands for hyperspectral image feature selection)

包含了信息融合领域近几年有影响力的多篇国内外文献(Contains many articles of influential domestic and international literaturethe in the field of information fusion in recent years, )

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 .)

说明：  matlab书上第六章数值运算的几个样例习题。。。。。(the descirbtion of the matlab)

matlab程序求相关系数数字图像相关法是对全场位移和应变进行分析的一种新的实验力学方法 (matlab program seeking correlation coefficient Digital image cross-correlationmethod (DIC) is a newmethod ofexperimentalmechanics for the analysis ofwhole field displacement and strain. Image processing is one of the cores ofDIC. )

线阵ccd信号处理，信号放大预处理，采样保持，A/D转换，分析采集的到的图像信息，确定物体位置(signal prosessing of ccd)

说明：  slic超像素分割，可以实现图像的超像素分割(SLIC super pixel segmentation)

Fast Discrete Curvelet Transform有正反变换,各个程序里面的参数都有详细的说明.(Fast Discrete Curvelet Transform are pros and transform, inside the various parameters have detailed explanations.)

处理Gamma乘性噪声的PPB方法，考虑了非局部patch的相似性，可处理SAR图像去噪。(The PPB method for multicative noise removal, which based on the Probabilistic Patch similarity.)