[1]刘政清,杨华,范彬,等.基于最大模糊熵的红外图像边缘检测算法[J].红外技术,2007,29(1):047-50.
 LIU Zheng-qing,YANG Hua,FAN Bin,et al.Edge Detection of Infrared Image Based on Maximum Fuzzy Entropy[J].Infrared Technology,2007,29(1):047-50.
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基于最大模糊熵的红外图像边缘检测算法
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《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
29卷
期数:
2007年第1期
页码:
047-50
栏目:
出版日期:
2007-01-20

文章信息/Info

Title:
Edge Detection of Infrared Image Based on Maximum Fuzzy Entropy
文章编号:
1001-8891(2007)01-0047-04
作者:
刘政清杨华范彬同武勤
解放军电子工程学院安徽省红外与低温等离子体重点实验室,安徽 合肥 230037
Author(s):
LIU Zheng-qingYANG HuaFAN BinTONG Wu-qin
Key Lab of Infrared and Low Temperature Plasma of Anhui Province, Electronic Engineering Institute, Hefei Anhui 230037, China
关键词:
边缘检测红外图像模糊熵模糊划分
Keywords:
edge detectioninfrared imagefuzzy entropyfuzzy partition
分类号:
TP391.4
文献标志码:
A
摘要:
针对红外图像边缘检测这一难题,结合红外图像及其梯度图像的特点,在红外梯度图像模糊划分的基础上,提出了一种基于最大模糊熵的红外图像边缘检测方法。首先通过改进传统Sobel算子构造出红外图像的梯度图并研究其直方图特点,然后对其进行自然模糊划分,最后根据最大模糊熵准则确定最优模糊参数,进而确定梯度图像的最佳分割阈值,从而实现边缘提取。与传统的基于梯度的边缘检测算法进行对比实验,结果表明,该方法用于红外图像边缘检测能获得更好的效果。
Abstract:
Pointing at the difficulty in the edge detection of infrared image, the characteristics of the infrared image and its gradient image are analyzed. Through fuzzy partition to the gradient image, edge detection of infrared image based on maximum fuzzy entropy is introduced. First, the gradient image is constructed by improving the Sobel operator, and its characteristics is studied; then, implemented fuzzy partition to infrared gradient image; at last the optimal fuzzy parameter is obtained from the rules of maximum fuzzy entropy. At the same time, the optimal segmentation threshold value is achieved, and the edge detection is realized finally. The results show that the proposed approach has better performance than some classical edge detection methods based on gradient.

参考文献/References:

[1] ?孙伟, 夏良正, 潘泓. 一种基于模糊划分的边缘检测算法[J]. 中国图象图形学报. 2004, 9(1): 18~22.
[2] ?章毓晋. 图像分析(第2版)[M]. 北京: 清华大学出版社. 2005.
[3] ?R. Gonzalez, R. Wood, Digital Image Processing[M]. Addison-Wesley, 1992.
[4] ?金立左, 夏良正. 模糊划分熵的新定义及其在图像分割中的应用[J]. 红外与毫米波学报. 2000, 19(3): 219~223.
[5] ?Pal S K, King R A. On edge detection of X-ray images using fuzzy sets [J]. IEEE Trans., PAM I. 1983, 5(1): 69~77.
[6] ?吴嶶. 一种改进的模糊边缘检测算法[J]. 现代电子技术. 2002, (4): 46~48 .
[7] ?杨水超, 马志峰, 赵保军. 一种改进的模糊边缘检测快速算法[J]. ? 红外技术. 2005, 27(2): 139~142.
[8] ?郑毅, 刘上乾. 基于模糊指数熵和模拟退火的图像分割[J]. 红外技术. 2006, 28(7): 395~399.
[9] ?Y. H. Kuo, C. S. Lee, C. C. Liu. A New Fuzzy Edge Detection Method for Image Enhancement[J]. IEEE Int. Conference on Fuzzy Systems. 1997: 1069~1074.
[10] ?Dumitrescu D. Fuzzy measures and the entropy of fuzzy partition[J]. ? J. Math. Appl. 1993, 176: 359~373.
[11] ?唐英干, 刘冬, 关新平. 一种改进的模糊熵红外图像分割方法[J]. ?激光与红外. 2006, 36(4): 321~323.

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备注/Memo

备注/Memo:
?收稿日期:2006-11-05
作者简介:刘政清(1980-),男,江西高安人,电子工程学院硕士研究生。主要研究方向:红外图像处理及目标检测。

更新日期/Last Update: 2014-12-26