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基于二进小波和抗噪形态学的烟雾边缘检测算法
引用本文:高英姿,姚爱琴,孙运强,张丽娜.基于二进小波和抗噪形态学的烟雾边缘检测算法[J].机械与电子,2021,39(8):18-22.
作者姓名:高英姿  姚爱琴  孙运强  张丽娜
作者单位:中北大学信息与通信工程学院,山西 太原 030051
摘    要:针对枪口烟雾图像的不规则性以及烟雾扩散速度快等特点,传统的边缘检测算法无法高效地提取烟雾边缘轮廓的问题,对烟雾图像采集技术、烟雾图像预处理技术以及烟雾图像边缘检测技术进行了研究,提出了一种改进的二进小波和抗噪形态学融合的边缘检测算法.首先,在 B 样条二进小波基础上,将二进小波消失矩的阶数提高到四阶;其次,选取方向不同的结构元素,得出改进的形态学算子;最后,用小波逆变换重新构造枪口烟雾图像,对其进行锐化处理,输出边缘信息.仿真结果表明,该算法检测出来的枪口烟雾图像边缘定位准确且清晰完整,能有效抑制噪声,在客观方面优于传统的边缘检测算法.

关 键 词:二进小波  抗噪形态学  边缘检测  融合技术

Smoke Edge Detection Algorithm Based on Dyadic Wavelet and Anti Noise Morphology
GAO Yingzi,YAO Aiqin,SUN Yunqiang,ZHANG Lina.Smoke Edge Detection Algorithm Based on Dyadic Wavelet and Anti Noise Morphology[J].Machinery & Electronics,2021,39(8):18-22.
Authors:GAO Yingzi  YAO Aiqin  SUN Yunqiang  ZHANG Lina
Affiliation:( School of Information and Communication Engineering , North China University , Taiyuan 030051 , China )
Abstract:In view of the irregularity of muzzle smoke image and the fast speed of smoke diffusion , the traditional edge detection algorithm can not extract the smoke edge contour efficiently.This paper studies the smoke image acquisition technology , smoke image preprocessing technology and smoke image edge detection technology , An improved edge detectiona lgorithm based on the fusion of dyadic wavelet and anti noise morphology is proposed.Firstly , based on B-spline dyadic wavelet , the order of dyadic wavelet vanishing moment is increased to quartic ; Secondly , the improved morphological operator is obtained by selecting structural elements with different directions ; Finally , the muzzle smoke image is reconstructed by inverse wavelet transform , and the edge information is output by sharpening.The simulation results show that the edge of muzzle smoke image detected by the algorithm is accurate and clear , which can effectively suppress the noise , and is better than the traditional edge detection algorithm in the objective aspect.
Keywords:dyadic wavelet  anti noise morphology  edge detection  combinatorial technique
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