Infrared images segmentation based on the maximum cumulative residual entropy

XIE Peng-he; YANG Hui-xian; WANG Xu-si

doi:10.13873/j.1000-97872011.07.028

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Infrared images segmentation based on the maximum cumulative residual entropy

更新时间：2025-09-11

- Infrared images segmentation based on the maximum cumulative residual entropy
- Vol. 30, Issue 7, Pages: 34-37(2011)
- 作者机构：
  
  湘潭大学材料与光电物理学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872011.07.028
  CLC： TP391.41
- Published：2011
- 稿件说明：
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[1]谢鹏鹤,杨恢先,王绪四.基于最大累积剩余熵的红外图像分割[J].传感器与微系统,2011,30(07):34-37.

XIE Peng-he, YANG Hui-xian, WANG Xu-si. Infrared images segmentation based on the maximum cumulative residual entropy[J]. 2011, 30(7): 34-37.
[1]谢鹏鹤,杨恢先,王绪四.基于最大累积剩余熵的红外图像分割[J].传感器与微系统,2011,30(07):34-37. DOI： 10.13873/j.1000-97872011.07.028.

XIE Peng-he, YANG Hui-xian, WANG Xu-si. Infrared images segmentation based on the maximum cumulative residual entropy[J]. 2011, 30(7): 34-37. DOI： 10.13873/j.1000-97872011.07.028.

摘要

经典阈值化分割方法是常用的图像分割方法之一

但对于低对比度

低信噪比的红外图像分割效果不理想

将累积剩余熵运用于红外图像分割

即寻求使得累积剩余熵最大的灰度值作为分割阈值

实验结果表明:基于最大累积剩余熵的图像分割方法是一种有效的红外图像分割方法

比起经典的阈值分割方法

分割红外图像的效果要好。

Abstract

Classical thresholding method is one of the frequently used image segmentation method

but it can not obtain good segmentation result for infrared image with low contrast and low SNR.The cumulative residual entropy is applied to the infrared image segmentation.The method seeks gray value which make the maximum cumulative residual entropy as the threshold value.Experimental results show that the maximum cumulative residual entropy is an effective infrared image segmentation method

and can get better segmentation result for infrared image than the classical thresholding method.

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references

Otsu准则的阈值性质分析 [J]. 许向阳,宋恩民,金良海. 电子学报 . 2009(12)

基于二维最大熵和顺序滤波的红外图像分割 [J]. 郭清风,王建国. 红外技术 . 2008(02)

二维指数熵图像阈值选取方法及其快速算法 [J]. 潘喆,吴一全. 计算机应用 . 2007(04)

More on a New Concept of Entropy and Information [J] . Murali Rao. Journal of Theoretical Probability . 2005 (4)

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