registration

说明：  响应面三维可视化实现，可实现响应面图的交互式绘制。(3-D Visualization of Response Surface)

基于Fisher线性判别基础学习器的集成分类器专门用于数字媒体的隐写分析，目前使用高维特征空间。目前，由于其良好的检测精度和较小的计算成本，它可能是设计监督分类器用于数字图像隐写分析的最常用方法。(The ensemble classifier, based on Fisher Linear Discriminant base learners, was introduced specifically for steganalysis of digital media, which currently uses high-dimensional feature spaces. Presently it is probably the most used method to design supervised classifier for steganalysis of digital images because of its good detection accuracy and small computational cost. It has been assumed by the community that the classifier implements a non-linear boundary through pooling binary decision of individual classifiers within the ensemble.)

使用GC立体匹配算法生成视差图，内涵图片文件(GC disparity map)

说明：  该文件是MATLAB图形图象处理程序，对于学习MATLAB和做图形图象处理的哥们非常有用，次程序作为共享文件，请下载后勿作为商业用途，(MATLAB graphics image processing procedures, learning MATLAB graphics and image processing to do the Miners very useful meeting procedures as sharing files, please download not used for commercial purposes, thank you)

可以采用形态学方法找出边界，比较有益的初学者的学习方法。(It s very good for a newer to learning about image processing.)

条形码生成工具：利用此工具可自动生成条形码(Bar code generation tool)

利用matlab的DCT2函数，对图像做变换并压缩。并用8*8对图像分块，对每一块计算均方值作为阈值。(DCT2 use the matlab function, and transform the image so compressed. And 8* 8 image block, a calculation of each mean square value as a threshold.)

这是一个灰度图像进行哈夫曼编码的Matlab程序，包括编码和解码部分。绝对能用！(Huffman Code)

说明：  通过偏振进行图像处理和图像复原，利用大气光和物体反射光的光学模型进行复原(Image processing and restoration are carried out by polarization, and restoration is carried out by optical model of atmospheric light and object reflected light)

首先将非平稳的故障振动信号进行双树复小波包分解，得 到不同频带的分量；然后对每个分量求其峭度值和相关系数并进行比较；最后选取峭度值和相关系数较大的分量 进行软阈值降噪和双树复小波包重构，即可有效地消除振动信号中噪声的干扰，同时保留信号中的有效信息即实 现了故障特征信息的提取。(In view of the above situation, a new fault diagnosis method is proposed based on dual-tree complex wavelet packet transform and threshold de-noising. Firstly, the non-stationary fault signal is decomposed into several different frequency band components through dual-tree complex wavelet packet decomposition. Secondly, Kurtosis and the cross-correlation coefficient of each component are obtained and compared. Due to the kurtosis reflecting the signal variations, if the kurtosis value is bigger, the degree of the change of signal is bigger too. The correlation coefficient can reflect the proximity between the component and the original signal at the same time, the correlation coefficient is bigger, the more similar with the original signal. Finally, the components that have a bigger value are chosen to be de-noised by a soft threshold and reconstructed by dual-tree complex wavelet packet transform. The noise interference was eliminated effectively, and the effective si)