## 留言板

 引用本文: 范九伦, 雷博. 倒数粗糙熵图像阈值化分割算法[J]. 电子与信息学报, 2020, 42(1): 214-221.
Jiulun FAN, Bo LEI. Image Thresholding Segmentation Method Based on Reciprocal Rough Entropy[J]. Journal of Electronics and Information Technology, 2020, 42(1): 214-221. doi: 10.11999/JEIT190559
 Citation: Jiulun FAN, Bo LEI. Image Thresholding Segmentation Method Based on Reciprocal Rough Entropy[J]. Journal of Electronics and Information Technology, 2020, 42(1): 214-221.

## 倒数粗糙熵图像阈值化分割算法

##### doi: 10.11999/JEIT190559

###### 通讯作者: 雷博　leileibo@xupt.edu.cn
• 中图分类号: TP391.4

## Image Thresholding Segmentation Method Based on Reciprocal Rough Entropy

Funds: The National Natural Science Foundation of China(61671377, 61571361, 61601362), The Project of New Star Team of Xi’an University of Posts & Telecommunications (xyt2016-01)
• 摘要:

基于粗糙集理论的粗糙熵阈值法不需要图像之外的先验信息。粗糙熵阈值法需要解决两个问题，一是图像信息不完整性的度量，二是图像的粒化。该文基于倒数信息熵，提出一种倒数粗糙熵用来度量图像中信息的不完整性。为了更好地对图像进行粒化，采用一种基于均匀性直方图的粒子选取方式。该文提出的倒数粗糙熵表述简洁，计算简单。实验验证了该文方法的有效性。

• 图  1  cameraman 图像的直方图和均匀性直方图

图  2  均匀性直方图及最小峰宽度

图  3  NDT image1分割结果

图  4  NDT image2分割结果

图  5  OTCBVS\库5\irw02\000215分割结果

图  6  OTCBVS\库5\irw06\000225分割结果

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##### 出版历程
• 收稿日期:  2019-07-25
• 修回日期:  2019-10-25
• 网络出版日期:  2019-11-13
• 刊出日期:  2020-01-21

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