提出了基于最大互信息熵且具有奇数约束的优化得分函数。
A score function for optimization based on maximum mutual information entropy with odditional restriction is proposed.
结合信息论理论，提出了采用互信息熵来度量和评价测量效果，形成了测量信息的基本概念。
Combined with the information theory, the measurement effect can be evaluated by interactive information entropy, so the concept of measurement information is proposed.
医学图像融合的效果评价方法有很多，如信息熵、互信息、均方值、峰值信噪比和平均梯度等。
There are many kinds of image fusion methods, such as information entropy, mutual information, mean square error, peak signal to noise ratio and mean grads.
MEFS在基于最大熵原理的基础上，运用互信息和Z -测试技术，采用两步方法进行空间特征选择。
Based on the theory of maximum entropy, MEFS USES mutual information and Z-test technologies, and takes two-step method to execute feature selection.
通过将它与采用熵和联合熵的评价方法相比较，实验结果表明交互信息量是一种很好的评价方法。
Compared with the evaluation method of entropy and joint entropy, it was shown that mutual information was a good evaluation criterion.
本文在信息熵和互信息的基础上，提出了非线性偏自相关的定义。
Based on information entropy and mutual information, we proposed the definition of nonlinear partial autocorrelation.
简要地介绍了不确定性、信息熵、联合熵、条件熵、互信息的基本概念。
The basic concepts of uncertainty, information entropy, united entropy, term entropy and mutual information were introduced briefly.
这四种特征选择采用的统计方法是：卡方、信息增益、互信息、交叉熵。
The four kinds of feature selection statistics include Chi-square, information gain, and mutual information and cross entropy, and the four corresponding feature sets are obtained.
采用部分体积插值法和香农熵计算得到的互信息，无法避免会出现一些局部极值，可能导致错误的配准。
For the mutual information calculated by partial volume interpolation method and Shannon entropy, certain local extremums are inevitable, which may lead to inaccurate registration.
提出了一种用加权熵代替香农熵的互信息计算方法，并将其应用于图像配准实验。
Weighted entropy instead of Shannon entropy to compute the mutual information is proposed in this paper, and it has been used in medical image registration experiment.
并采用熵、交叉熵、互信息、均方根误差和峰值信噪比等指标对该方法进行了客观评价。
The method "s performance is evaluated by using the entropy, cross-entropy, mutual information, error of mean square root and peak signal to noise ratio."
介绍了图像融合的各种评价方法，包括：熵、交叉熵、交互信息量、均方误差、均方根误差、峰值信噪比。
The methods of the evaluation of image fusion, which includes: entropy, cross entropy, mutual information, mean square error, root mean square error, peak-to-peak signal-to-noise ratio were presented.
介绍了图像融合的各种评价方法，包括：熵、交叉熵、交互信息量、均方误差、均方根误差、峰值信噪比。
The methods of the evaluation of image fusion, which includes: entropy, cross entropy, mutual information, mean square error, root mean square error, peak-to-peak signal-to-noise ratio were presented.
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