37724107contourlet_toolbox

visualC 数字图像模式识别与技术详解，书籍源码部分。(visual C digital image pattern recognition and techniques detailed books source parts.)

应用投影算法对TV模型快速求解，并将算法应用到图像去噪中(The projection algorithm is used to solve the TV model quickly, and the algorithm is applied to image denoising)

冈萨雷斯数字图像处理MATLAB版，是我们学习图像处理必备的书籍(Gonzales digital image processing MATLAB version, we study the image processing necessary books)

说明：  一个很有用的Markov Decision Process matlab程序(a very useful Markov Decision Process procedures Matlab)

说明：  机器视觉中三维重建的源码 具体包括4个文件，其中.c文件用于产生图像特征点矩阵(In the three-dimensional reconstruction process, resulting in the source image feature dot matrix)

此matlab程序用于横向和纵向都被剪碎的纸片的拼接复原，高质量(This matlab program is used for the stitching of both horizontal and vertical pieces that are cut and broken, and of high quality)

在灰度图像中进行直线检测，带实验效果图像。利用快速Hough变换，能够正确查找线段端点。(In the gray image in a straight line detection, the experiment with the effect of the image. Using fast Hough transform, to correctly segment endpoint search.)

边缘图象分割程序，是使用vb编程，希望有帮助(edge image segmentation procedures, the use of vb programming, with the hope of helping)

《数字图像处理（第三版）》，中文版，作者是（美）冈萨雷斯，本书是数字图像处理经典著作。("Digital Image Processing (3rd Edition)", Chinese Edition, by Gonzalez, USA. This book is a classic work of digital image processing.)

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)