Filter.Solutions.v8.1

说明：  实现图片、文本隐藏在图片中，并导出等操作(Implement images, text hidden in images, and export operations)

说明：  基于压缩传感的图像处理，其中运用了迭代的方法，不错的文章(Based on compressed sensing image processing, which used the iterative approach, a good article)

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)

用wpf实现一个简单的手滑切换图片的实例

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 .)

数据文件以图像的格式打开，针对labview采集的图像以数据txt格式保存的。(Image data file format open , labview image acquisition for the data saved in txt format . )

处理计算机视觉中图像分析的图像轮廓检测和分层图像分割问题(Image processing computer vision analysis of image contour detection and hierarchical image segmentation)

目标检测，利用上下文关系 (object detection using context)

利用偏振片旋转三个不同角度得到的三幅偏振图像，计算求得偏振度图像和偏振角图像及斯托克斯分量图像(Use polarizer is rotated three different angles of the three polarization image, the image of the degree of polarization and polarization angle images calculable and Stokes component image)

用于植物叶片分类的图形界面,是Matlab源码，用BP神经网络实现(For plant leaf classification graphical interface, the Matlab source code, using BP neural network)