Based on maximum between-cluster variance method and uniformity measure, this paper USES maximum entropy principle to select the gray-level threshold value for image segmentation.
在最大类间方差法和一致性准则法的基础上，运用最大熵原理来选择灰度阈值对图像进行分割。
Entropy thresholding method is an automatic technique for thresholding of digital images based on gray level-gradient co-occurrence matrix and the maximum entropy principle.
它包括二维匹配滤波预处理以增强血管的灰度，以及用灰度-梯度共生矩阵的最大熵阈值化方法。
In this paper a novel method is presented to segment gray level image through maximizing the fuzzy partition entropy of two-dimensional histogram.
该文提出了一种通过最大化二维直方图模糊划分熵分割灰度图像的新算法。
In this paper, an automatic approach for thresholding based on gray level gradient co occurrence matrix model and the maximum entropy principles is proposed.
提出了一种基于灰度-梯度共生矩阵模型和最大熵原理的自动阈值化方法。
The results demonstrate that the maximum local entropy value decision criterion has a better performance than the gray level decision criterion for the segmentation.
实验结果表明，用图像局部熵相似性判决准则的图像分割结果优于用图像灰度值相似性判决准则的图像分割结果。
Combining the two essential characteristics of the image, the gradient and the gray level, a threshold segmentation approach using maximum entropy with the gradient boundary control was proposed.
结合梯度和灰度这两种图像的本质特征，提出一种基于边界梯度控制的最大熵阈值分割方法。
Combining the two essential characteristics of the image, the gradient and the gray level, a threshold segmentation approach using maximum entropy with the gradient boundary control was proposed.
结合梯度和灰度这两种图像的本质特征，提出一种基于边界梯度控制的最大熵阈值分割方法。
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