change detection with IDL

此MATLASB源代码是LSB的图像数字水印的嵌入与检测，希望对需要者有用!(This source code is MATLASB image watermarking LSB embedding and detection, in the hope that those who need it useful!)

这是一个地震数据多尺度分析和处理的文章.内容相当丰富,不仅仅增加地质方面的知识,更重要的是可以学到很多数据处理和小波分析方面的知识.(This is a multi-scale seismic data analysis and processing of the article. Fairly rich, is not only increasing geological knowledge, the more important it is to learn a lot of data processing and wavelet analysis knowledge.)

初步的代码，只保存边界的声波逆时偏移 RTM

Tarel和Hautiere的图像去雾方面的程序，去雾效果很不错，对于研究很在参考价值。(Tarel and Hautiere image to the fog of program, go to mist effect very good, to study in a reference value. )

一种基于节点密度分割和标签传播的Web页面挖掘方法(A mining based on node density segmentation and labeling dissemination of Web pages)

获取图像的LBP特征：对图像的原始LBP模式、等价LBP模式、旋转不变LBP模式，以及等价旋转不变LBP模式的LBP特征进行提取以及显示(Obtaining LBP features of images: extracting and displaying the original LBP pattern, equivalent LBP pattern, rotation invariant LBP pattern and equivalent rotation invariant LBP pattern of images)

PCA+LDA人脸识别，识别率高于单独PCA或LDA算法。需要matlab dimension reducation toolbox。(Face verification using PCA and LDA fusion. Better performance than single PCA or LDA algorithm. The image database is included. Matlab dimension reduction toolbox is requrired. )

完成对视频帧的四叉树分割，在纹理复杂处分割块较小，在纹理平坦处分割较大(Complete quadtree segmentation of video frames, complex area in texture segmentation smaller, flat larger regional segmentation block in texture)

图像融合中常用的评价指标（非常全面）如：平均梯度、相关系数、信息熵、交叉熵、联合熵、均方误差、互信息、信噪比、峰值信噪比、均方根误差、空间频率、标准差、均值、扭曲程度、偏差指数等等。(Image fusion evaluation (very comprehensive): average gradient, correlation coefficient, entropy, cross entropy, joint entropy, mean square error and mutual information, signal to noise ratio, peak signal to noise ratio, root mean square error, spacefrequency, standard deviation, mean, distorting the degree of deviation index.)

SIFT特征提取演算法(包含匹配以及除错机制RANSAC)-可用于两张影像之特征点匹配 (SIFT feature extraction algorithm (including the match, as well as debug mechanisms RANSAC)- can be used for two images of the feature points matching)