...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The American statistician >Average Entropy: A New Uncertainty Measure with Application to Image Segmentation
【24h】

Average Entropy: A New Uncertainty Measure with Application to Image Segmentation

机译：平均熵：一种新的不确定性度量及其在图像分割中的应用

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Various modifications have been suggested in the past to extend Shannon entropy to continuous random variables. This article investigates these modifications, and suggests a new entropy measure with the name of average entropy (AE). AE is more general than Shannon entropy in the sense that its definition encompasses both continuous as well as discrete domains. It is additive, positive and attains zero only when the distribution is uniform. The main characteristic of the suggested measure lies in its consistency behavior. Many properties of AE, including its relationship with Kullback-Leibler information measure, are studied. Precise theorems about the vanishing of the conditional AE for both continuous and discrete distributions are provided. Toward the end, the measure is tested for its effectiveness in image segmentation.
机译：过去已经提出了各种修改以将香农熵扩展到连续随机变量。本文研究了这些修改，并提出了一种新的熵测度，命名为平均熵（AE）。 AE比Shannon熵更笼统，因为它的定义既包含连续域也包含离散域。它是加性的，为正，仅当分布均匀时才为零。建议措施的主要特征在于其一致性行为。研究了AE的许多特性，包括其与Kullback-Leibler信息测度的关系。提供了有关连续分布和离散分布的条件AE消失的精确定理。最后，测试该措施在图像分割中的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号