total-variation-denoising

图像剧烈湍流模糊，数字图像处理（第二版）第五章例题5.25的实现程序(Severe turbulence fuzzy image, digital image processing (second edition), Chapter V, Example 5.25, to achieve program)

包含实验图片，实验代码,对于从事数字图像处理工作有一定帮助(including experimental images and agrithms.It is benificial to image procecing workers.)

说明：  简易的在c#中利用gdal来读取遥感图像(Using GDAL to read remote sensing image in C)

简单的图形文字识别软件，希望大家喜欢我的分享，谢谢(Simple graphical text recognition software, I hope you like my share, thank you)

说明：  本文以k-means算法为背景，引入信息熵相关知识，从而实现全自动分割图像。然而在利用混合高斯模型对图像进行数据分析时，会发生一定的过拟合现象，导致我们得不到预期的聚类数目。本文设计合理的合并准则，令模型简化，有效地消除过拟合现象，使得最后得到的聚类数目与预期符合。，设计合理的准则改进了图像的全自动分割方法，使得分割结果更加优化(In this paper, k-means algorithm is used as the background, and information entropy related knowledge is introduced to realize full-automatic image segmentation. However, when the Gaussian mixture model is used to analyze the image data, there will be some over-fitting phenomenon, resulting in that we cannot get the expected number of clusters. In this paper, a reasonable merging criterion is designed to simplify the model and effectively eliminate the over-fitting phenomenon, so that the final clustering number is in line with the expectation. A reasonable criterion is designed to improve the automatic image segmentation method and make the segmentation result more optimized.)

图像分割的matlab程序，以及其他的一些程序。希望能对大家有用，如有错误请谅解。(Matlab image segmentation procedures and other procedures. We hope that it can be useful if there is an error, please understanding.)

DWT域的水印提取，matlab 以及信噪比分析(DWT watermark extraction, and signal-to-noise ratio analysis Matlab)

该程序是一种最小均方误差滤波算法的matlab实现，主要应用于干扰对消方面(The program is a minimum mean square error filtering algorithm matlab realize, mainly used in interference cancellation)

tv图像修复，用matlab实现，包含源图像以及修复后的图像，有文字修复，划痕修复，小斑点修复等。(TV image restoration, using matlab implementation, including the source image and the image after the repair, the text repair, scratch repair, spot repair.)

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 )