EASI

将dct生成的8*8块图像数据进行zigzag排序，以及恢复算法，在脆弱水印中使用。(The program zigzag sort 8*8 image data generated by dct, and restore algorithm, which is used in fragile watermarking.)

基于opencv实时图像的2值化处理，一定要有摄像头(Opencv-based real-time image processing of two values, there must be a camera)

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 .)

将一幅图像以jpeg的形式进行压缩，对初学者很有用(Jpeg form of an image compression, very useful for beginners)

计算一副图像，或者加噪声后图像信噪比和峰值信噪比，代码非常简洁方便，效率很高。(Calculate the image SNR and PSNR)

matlab中dftfilt.m文件函数源代码(Matlab dftfilt.m file function source code)

程序实现了三种去噪算法：BLS-GSM/BM3D/NLM，评价指标为PSNR/SSIM.(Program implements three de-noising algorithm: BLS-GSM/BM3D/NLM, with evaluation of PSNR/SSIM.)

有效地MR图像重建算法，主要用于在MR图像的成像过程中对图像进行压缩(Efficient MR Image Reconstruction for Compressed MR Imaging)

CT图像的平行束重建图像的重建算法，非常高(CT image parallel beam reconstruction image reconstruction algorithm, very high)

从原始图像产生噪声图像，使用db1执行2层小波，使用wpbmpen进行全阈值选择，采用硬阈值和软阈值处理方式,保存低频,进行图像降噪，并绘制各分解系数图像。(Generated noise image from the original image, using db1 wavelet perform two layers using wpbmpen full-threshold selection, using hard threshold and soft threshold approach, saving low frequency, image noise reduction, and draw the decomposition coefficients images.)