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基于信息熵的X射线弹药图像自适应局部模糊增强
引用本文:徐美芳,王浩全,桂志国.基于信息熵的X射线弹药图像自适应局部模糊增强[J].无损检测,2010(12):940-943.
作者姓名:徐美芳  王浩全  桂志国
作者单位:中北大学仪器科学与动态测试教育部重点实验室,太原030051
基金项目:山西省自然科学基金资助项目(2009011020-2); 山西省高校科技开发项目(200713013); 中北大学2008年校青年科学基金资助项目
摘    要:针对X射线弹药图像对比度较低、缺陷边缘模糊的特点,提出了一种基于信息熵的自适应局部模糊增强算法。该方法先对弹药射线图像进行动态归一化处理,并运用梯度算子获取感兴趣区域,OTSU算子自动选取最佳渡越点gc,从而得到模糊增强算子的渡越点cμ,再使用改进的隶属函数对cμ两侧的像素灰度进行模糊域的非线性处理,从而得到增强后的弹药图。试验结果表明,该算法能明显提高弹药图像的对比度,突出疵病并降低背景噪声。

关 键 词:自适应增强  模糊信息处理  隶属函数  X射线图像

An Adaptive Local Fuzzy Enhancement Approach Based on Information Entropy for X-Ray Ammunition Image
XU Mei-Fang,WANG Hao-Quan,GUI Zhi-Guo.An Adaptive Local Fuzzy Enhancement Approach Based on Information Entropy for X-Ray Ammunition Image[J].Nondestructive Testing,2010(12):940-943.
Authors:XU Mei-Fang  WANG Hao-Quan  GUI Zhi-Guo
Affiliation:(Key Lab of Instrumentation Science and Dynamic Measurement(North University of China),Ministry of Education,Taiyuan 030051,China)
Abstract:For the problems of the low contrast and fuzzy flaw edge in X-ray ammunition image,an adaptive local fuzzy enhancement approach based information entropy was presented.It first dynamically normalized the ammunition image,obtained the regions of interest by gradient operator,and automatically selected the best crossover point gc with OTSU algorithm in order to get the transition μc of fuzzy enhancement operator.It then used the improved membership function to nonlinearly fuzzy process the gray value on the two sides μc to obtain the enhanced ammunition image.Experimental results demonstrated that the proposed approach could efficiently improve the contrast of the ammunition image and enhanced the flaw information.
Keywords:Adaptive enhancement  Fuzzy information processing  Membership function  X-ray image
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