基于隶属度函数的电力设备红外图像模糊增强算法研究
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摘要
为解决红外图像噪声、对比度等对电力设备红外热像诊断结果的影响,本文提出一种基于Logistic隶属度函数的红外图像模糊增强算法。通过对设备红外热像进行双边滤波后,运用基于Logistic隶属度函数的模糊理论进行模糊化,并对所得模糊域内图片进行增强及去模糊处理,得到了增强效果明显的红外热像。结果表明,相对传统的几种隶属度函数等处理算法,本文方法处理后的红外图像边缘信息更为完整、图像对比度大幅提高。本算法执行效率高,可实现电力设备红外热像的批量处理以及设备的故障诊断。
In order to enhance the contrast of infrared image of electric power equipment,to highlight the fault section,and to help the human observers and machine perception,a fuzzy enhancement technology of infrared image based on Logistic function was proposed. After bilateral filtering of infrared image,fuzzy transformation using Logistic membership value and fuzzy enhancement were processed. Finally,the image was de-fuzzed.Experimental results show that the effect of proposed method is better than the classic ones,and the integrality of edge-information and image contrast can be improved. It is beneficial for both maintainers and machines to locate and identify the fault.
In order to enhance the contrast of infrared image of electric power equipment,to highlight the fault section,and to help the human observers and machine perception,a fuzzy enhancement technology of infrared image based on Logistic function was proposed. After bilateral filtering of infrared image,fuzzy transformation using Logistic membership value and fuzzy enhancement were processed. Finally,the image was de-fuzzed.Experimental results show that the effect of proposed method is better than the classic ones,and the integrality of edge-information and image contrast can be improved. It is beneficial for both maintainers and machines to locate and identify the fault.
引文
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[12]王一帆,尹传历,黄义明,等.基于双边滤波的图像去雾[J].中国图象图形学报,2014,19(3):386-392.
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[15]王宇庆,王索建.红外与可见光融合图像的质量评价[J].中国光学,2014,7(3):396-401.
[2]裴福俊,程雨航,李昊洋,等.基于空间域划分的分布式SLAM算法[J].系统工程与电子技术,2015,37(3):639-645.
[3]许艳.图像的频域滤波增强研究与仿真[J].电子技术,2013,42(12):13-15.
[4]李庆忠,刘清.基于小波变换的低照度图像自适应增强算法[J].中国激光,2015,42(2):280-286.
[5]黄小丹.基于拉普拉斯金字塔变换的小波域图像融合[J].电子科技,2014,27(6):170-173.
[6] Surya PrabhaD,Satheesh KumarJ. An efficient im-age contrast enhancement algorithm using geneticalgorithm and fuzzy intensification operator[J].Wire-lessPersonalCommunications,2017,93(1):223-244.
[7]宋欢欢,李雷.基于模糊熵的两种图像增强技术[J].计算机技术与发展,2013,23(6):67-70.
[8]云海姣,吴志勇,王冠军,等.结合直方图均衡和模糊集理论的红外图像增强[J].计算机辅助设计与图形学学报,2015,27(8):1498-1505.
[9]徐年,李伟,陈飞,等.基于模糊理论的地震现场图像增强技术研究[J].地震工程学报,2016,38(S1):134-137.
[10]姜庆伟,田媛.模糊理论图像增强快速算法设计与实现[J].电子测试,2013(10):19-21,34.
[11]赵春晖,刘振龙.基于模糊集理论的图像增强算法[J].黑龙江大学自然科学学报,2012,29(3):401-406.
[12]王一帆,尹传历,黄义明,等.基于双边滤波的图像去雾[J].中国图象图形学报,2014,19(3):386-392.
[13]张勇,金伟其.夜视融合图像质量客观评价方法[J].红外与激光工程,2013,42(5):1360-1365.
[14]张剑英,汪一,张跃辉.色度在评价增强图像时对传统算法的修正效果[J].电视技术,2016,40(9):100-102,136.
[15]王宇庆,王索建.红外与可见光融合图像的质量评价[J].中国光学,2014,7(3):396-401.