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一个基于互信息的图像配准源代码，采用粒子群优化算法源代码，可直接使用。-A mutual information based image registration source code, using particle swarm optimization algorithm source code can be used directly.
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计算两幅图像的互信息和联合直方图，适于图像处理初学者，,Calculation of two images of the mutual information and joint histogram, image processing is suitable for beginners,
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图像配准，利用互信息进行图像配准，主要针对旋转和平移,Image registration using mutual information for image registration, the main response to rotation and translation
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混沌计算程序源文件——包括计算Lyapunov指数的5种方法：C-C算法,最小数据量算法，G-P算法，关联维数法，互信息量法。,the original programs to calculate chaos in order to count the Lyapunov index out. Including 5 such methods: c-c method, minimum data method, G-P, mutual information method and correlati
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利用互信息进行特征抽取的方法实现，能找到最具代表的特征，有效的实现了计算量的减少和可用来维数缩减-The use of mutual information feature extraction method of implementation, to find the most representative characteristics of an effective implementation of the computation of the reduction and can be
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基于互信息理论的最大相关排序算法，可应用于各领域的特征选择。-Maximum mutual information based relevance ranking algorithm theory can be applied to all areas of feature selection.
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该代码是基于互信息的非均匀特征排序算法的MATLAB实现-The code is based on the mutual information of non-uniform features of MATLAB realization of sorting algorithms
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这是一个关于基于互信息的图像配准程序，是以matlab编写-This is a mutual information based image registration procedures, the preparation is matlab
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基于互信息的图像配准，使用pso和powell优化算法，GUI界面，proj.m-Based on mutual information image registration, use the pso and powell optimization, GUI interfaces, proj.m
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非刚性图像配准算例，包括最速梯度下降优化、二次样条、2D/3D配准、互信息最小化、3D仿射等多种配准算法。
非刚性配准是当前应用最多的配准方法，用于处理有较大位移的配准问题-Non-rigid image registration examples, including the steepest gradient descent optimization, quadratic spline, 2D/3D registration, mutual information minimizatio
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基于K均值算法和互信息熵差的算法，可以有效地确定分类数,从而该算法对医学图像进行自动优化分割。-K means algorithm based on entropy and mutual information algorithms, can effectively determine the classification number, so that the algorithm for automatic optimization of medical image segmentation.
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计算互信息，非常详细，在网上很少有的-Calculation of mutual information, very detailed, in-line rare! ! !
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这是从网上整理出来的图像融合评价标准，总共有13项性能指标。包括平均梯度，边缘强度，信息熵，灰度均值，标准差(均方差MSE)，均方根误差，峰值信噪比（psnr），空间频率(sf)，图像清晰度，互信息(mi)，结构相似性(ssim)，交叉熵(cross entropy)，相对标准差。大家一起交流吧~-This is sorted out from the online image fusion evaluation criteria, there are a total of 13 perform
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计算熵值，互信息 自信息 香农编码 费诺编码 包含源代码-Calculate the entropy, mutual information contains the source code from the information the Shannon encoded Fenno coding
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互信息：计算两幅图像之间的互信息-Mutual information: calculating the mutual information between two images
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基于互信息的图像匹配程序，使用powell算法，pv插值法。应用在医学图像的配准领域-Mutual information-based image matching procedures, the use powell algorithm, pv interpolation. Used in the field of medical image registration
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贝叶斯（Bayesion）机器学习相互信息。用于求取熵、联合熵等。改进后可用于随机反演-Bayesian (Bayesion) machine learning of mutual information. Used to obtain entropy, joint entropy and so on. Improved can be used for stochastic inversion
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用matlab编写的基于轮廓最大互信息图像配准算法-Prepared using matlab contour based on the maximum mutual information image registration algorithm
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利用互信息法求延迟，可用于求解信号的相空间-The use of mutual information method delayed, can be used to solve the signal phase space
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对图像进行计算互信息，从而进行影像匹配。互信息非常适合多源遥感影像的匹配，改算法非常适用-The image calculated mutual information, thus to image matching. Mutual information is ideal for multi-source remote sensing image matching algorithm is very applicable to
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