kalmanXYZT.m

给图像加椒盐和高斯噪声，以及空域滤波（中值和均值滤波）！(to Image pretzels and Gaussian noise, and the spatial filter (mean values and filter)!)

指纹图像增强，gabor滤波器，包括形态学分割，形态学细化，加窗短时傅里叶变换增强，方向图估计及平滑，纹线频率估计及平滑(Fingerprint image enhancement, gabor filters, normalization, equalization, morphological segmentation, morphological thinning, windowed short time Fourier transform enhanced estimates and smooth pattern, ridge frequency estimation and smoothing)

对图像进行GMM（混合高斯）拟合后用EM算法进行分割(Image GMM (Gaussian Mixture) after fitting algorithm using EM Segmentation)

图像的傅里叶变换。在代码中实现了将两幅图像的幅度谱和相位谱进行交换，进而理解两者在图像显示中的作用(Fourier transform of the image. Implemented in the code will be two images amplitude spectrum and phase spectrum of exchange, and thus to understand both the role of the image display)

说明：  一个机载SAR的成像算法，SAR的点目标RD成像算法(An airborne SAR imaging algorithm, SAR point target imaging algorithm RD)

基于DCT域的鲁棒水印，能抗击一定程度的压缩，剪切等攻击(Based on the DCT domain robust watermarking, can fight against a certain degree of compression, shear, such as attacks)

來自於2012年IEEE TIP的論文 Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution ，其功能為透過分析影像中的直方圖統計資訊，達到快速增強影像對比的結果。(From the 2012 IEEE TIP paper "Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution"which functions as a histogram of the image by analyzing statistical information, to quickly enhance image contrast.)

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 .)

采用SVD方法进行人脸特征提取,希望对大家有用(SVD method using facial feature extraction, in the hope that useful to everybody)

图像修复的改进算法，RPCA算法程序代码，实现图像的去噪和复原(Improved algorithm of image restoration, RPCA algorithm program code, to achieve image denoising and restoration)