PNLM

适合各类图象， 手动选择感兴趣目标区域，使用于图象图象处理，同时包含一区域生长程序。(Suitable for all types of images, manually select the target region of interest, the use of image processing in the image at the same time contains a region growing procedure.)

简单水印制作源码,程序结合易语言扩展界面支持库，实现了加载水印效果图和设置水印效果的功能(Simple watermarking source code , the program combined with easy language support library expansion interface , to achieve a load diagram and set watermark watermark function)

详细介绍了matlab下的曲线和曲面拟合，并有一份word的原理说明，介绍的很详细，可供参考和实际运用(Described in detail under the matlab curve and surface fitting, and a word there is the principle that the very detailed introduction is available for reference and practical use of)

点扩散函数，matlab程序，图像处理中的应用举例(Point spread function, matlab program, application examples in image processing)

提出了一种基于非下采样Contourlet 变换的自适应图像去噪方法 首先对噪声图像进行非下采样Contourlet 变换，得到各 个尺度各个方向子带的系数，再根据该系数的能量自适应地调整去噪阈值 实验表明，与Contourlet 多尺度阈值去噪 Contourlet 自 适应阈值去噪相比，该方法在保留图像边缘细节的同时，能提高图像的PSNR 值，减少了Gibbs 现象(A new adaptive method of image de-noising based on NonSubsampled Contourlet Transform （NSCT）is presented.Firstly， the noisy image is decomposed into a set of multiscale and multidirectional frequency subbands by NSCT， and then the threshold is adapted automatically according to the energy of subband coefficients.Compared with the multi-scale threshold using contourlet transform and using adaptive threshold based on contourlet transform， the simulation results show that the performance of this method is superior in PSNR， meanwhile it can maintain the image edge and reduce the Gibbs phenomen)

db4小波的提升小波分解，从已发表的论文中得来，可放心使用(db4 wavelet lifting wavelet decomposition, the published papers come, you can be assured)

全参考型视频质量评价方法，基于机器学习和视频特征提取，发表与2012年TMM(FR VQA method based on machine learning and video feature )

视频中运动的放大，欧拉运动放大,包含事例视频，以及代码使用方法。(Enlarge video motion, Euler motion amplification, contains examples of video, as well as the code to use.)

利用opencv库写的一个关于图像孔洞填补的小程序，附加了效果图片(Using the opencv library to write a small program on the filling of the hole, the additional effect of the picture)

完整正确的仿射变换程序，测试过绝对没有错(Complete the correct affine transformation procedures, the test had absolutely nothing wrong with)