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SNS_matlab-master
图像重定向源代码，本文提出一种网格变形框架，允许显著特征进行均匀缩放，从而保证图像内容的完整性，将变形分布到不重要的区域。(The source code of optimal scale stretching image redirection is presented, and an effective image redirection algorithm is proposed to better guarantee the integrity of the image.)
- 2021-05-14 18:30:03下载
- 积分：1
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RegisterandFusion
波变换的图像配准与融合算法的研究，主要描述了图像的各种配准方法和基本的融合方法(Wavelet transform algorithm for image registration and fusion research, will describe a variety of image registration methods, and basic integration methods)
- 2010-03-12 16:14:35下载
- 积分：1
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release
眼球追踪算法 matlab实现 内含说明pdf(eyetracking m file with introduction)
- 2020-09-28 10:57:45下载
- 积分：1
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Face Description with LBP MATLAB
说明： LBP模式下的人脸识别方法，matlab范例，有论文说明，LBP算法(LBP mode of face recognition method, matlab example, there are papers, LBP algorithm)
- 2021-02-19 22:07:33下载
- 积分：1
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fuse_method
说明： 图象处理的融合算法集合,有8种融合算法,这是我硕士课题中的源代码.以函数的形式给出,肯定能用(The integration of image processing algorithm for the collection, there are eight kinds of fusion algorithm, this is my master s degree in the subject s source code. In the form of function is given, certainly can)
- 2008-10-21 08:39:30下载
- 积分：1
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hrrp_1
基于matlab的高分辨距离像的研究 svm实现(high ratio radar magic basic on matlab)
- 2009-09-25 05:17:54下载
- 积分：1
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svm
相当经典的一款SVM
可视化相当好，当今流行的2大SVM()
- 2008-05-10 20:45:14下载
- 积分：1
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trackingGUI
说明： 视频追踪的框架算法，实现了基于meanshift和feature based的跟踪算法(Framework for video tracking algorithm meanshift based and feature based tracking algorithm)
- 2008-10-21 01:14:33下载
- 积分：1
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SVDD_matlab
SVDD classifier 即支持向量数据描述分类器，能将数据分为两类。本文件也提供了训练数据和测试数据，方便进行测试。(Support vector data description classifier. Data can be divided into two categories .This document also provides training data and test data to make it easy to test the program.)
- 2017-06-23 12:02:08下载
- 积分：1
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dual-tree
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)
- 2014-05-28 17:02:14下载
- 积分：1
