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在保证图像质量的前提下，为了提高可逆信息隐藏的容量，提出了一种基于差值扩 展的可逆信息隐藏新算法(The premise of guaranteeing the image quality, in order to improve the reversible capacity of information hiding, a difference expansion based on new algorithm for reversible information hiding)

中值滤波，取出奇数个数据进行排序，用排序后的中值取代要处理的数据即可(median filtering.rar)

SVM算法的线性分类，图像分类单幅遥感图像特征提取分类(Linear classification of SVM algorithm, image classification, feature extraction and classification of single remote sensing image)

说明：  能精确的提取数字图像的轮廓。不管图形的形状如何，都能达到预期的效果。并且能将边界的坐标输出到一个文件中，供使用者分析数据。(Able to extract precise contours of the digital image. Regardless of the shape of how graphics can achieve the desired effects. The coordinates of the border and is capable of output to a file, for users to analyze data.)

Bandelet变换的图像处理工具箱，包括图像处理的源程序(Bandelet transform image processing toolbox, including image processing of the source)

VC计算机图形学原理及算法教程 VC计算机图形学入门教程(VC theory and algorithms of computer graphics computer graphics tutorial Tutorial VC)

在vs平台下利用opencv程序，可以处理图像的膨胀、腐蚀以及开闭运算。(Availability v Understanding use of open platform opencv degree, permissible processing, swelling, corrosion and opening and closing operation)

说明：  一个非常简小灵便的DICOM文件阅读器,支持多种格式的文件，支持图片的大多数编辑功能。(A very simple and handy DICOM file reader supports multiple formats of files and most editing functions of pictures.)

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)

局部二进制模式，LBP，是已被用于纹理特征的一个 分类。在本文中，提出了一种基于使用这些功能的方法 检测缺陷图案的面料。在培训阶段，在第一个步骤LBP算子是 施加到无缺陷织物样品，逐个象素和参考的所有的行（列） 特征矢量的计算。那么这个图像被分为Windows和LBP算子是 应用这些窗口的每一行（列）。根据与参考比较 特征向量一个合适的阈值，无缺陷的窗户被发现。在检测阶段中，一个 测试图像被划分成的窗户，并使用阈值时，有缺陷的窗口可以 检测到。该方法简单，灰度不变。由于其简单性， 线上实现是可能的。(Local Binary Patterns, LBP, is one of the features which has been used for texture classification. In this paper, a method based on using these features is proposed for detecting defects in patterned fabrics. In the training stage, at first step LBP operator is applied to all rows (columns) of a defect free fabric sample, pixel by pixel, and the reference feature vector is computed. Then this image is divided into windows and LBP operator is applied to each row (column) of these windows. Based on comparison with the reference feature vector a suitable threshold for defect free windows is found. In the detection stage, a test image is divided into windows and using the threshold, defective windows can be detected. The proposed method is simple and gray scale invariant. Because of its simplicity, online implementation is possible as well. )