基于改进小波变换的零件缺陷红外图像增强方法研究
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摘要
为解决使用红外无损检测技术对机械零件内部存在的缺陷进行检测时,获取的零件内部缺陷红外图像存在的噪声大、边缘模糊等问题,分别使用直方图均衡化以及基于小波变换的改进算法对红外无损检测实验中检测出的含有内部缺陷的红外图像进行图像增强。随后引入信噪比概念分别对直方图均衡化和改进算法做了对比。结果表明,本文改进算法抑制了目标缺陷区域的噪声以及非缺陷区域背景,使得缺陷区域图像视觉效果更好,为下一步图像分割提供了依据。
When the infrared nondestructive testing technology is used to detect the internal defects of mechanical parts, the acquired infrared image of the internal defects of the parts has big noise and fuzzy edges. Aiming at above problem, it uses the histogram equalization and an improved algorithm based on wavelet transform to enhance the infrared image with internal defects detected in the infrared nondestructive testing experiment, applies the concept of SNR to compare histogram equalization with the improved algorithm. The results show that the proposed improved algorithm restrains the noise of target defect region and the background of non-defect region, improves the visual effect of defect area image, provides a basis for the next step of image segmentation.
When the infrared nondestructive testing technology is used to detect the internal defects of mechanical parts, the acquired infrared image of the internal defects of the parts has big noise and fuzzy edges. Aiming at above problem, it uses the histogram equalization and an improved algorithm based on wavelet transform to enhance the infrared image with internal defects detected in the infrared nondestructive testing experiment, applies the concept of SNR to compare histogram equalization with the improved algorithm. The results show that the proposed improved algorithm restrains the noise of target defect region and the background of non-defect region, improves the visual effect of defect area image, provides a basis for the next step of image segmentation.
引文
[1] 于天河,郝富春,康为民.红外图像增强技术综述[J].红外与激光工程,2007(增刊2):131-137.
[2] 邢素霞.红外热成像与信号图像处理[M].北京:国防工业出版社,2011.
[3] 许开宇,李双一.基于小波变换的图像融合算法的实现[J].红外技术,2007,29(8):455-458.
[4] 潘泉,张磊,孟晋丽,等.小波滤波方法及应用[M].北京:清华大学出版社,2005.
[5] 谢杰成,张大力,徐文立.小波图像去噪综述[J].中国图像图形学报,2002,7(3):209-218.
[6] 尹士畅,喻松林.基于小波变换和直方图均衡的红外图像增强[J].激光与红外,2013,43(2):265-268.
[7] 李弼程,彭天强,彭波.智能图像处理技术[M].北京:电子工业出版社,2004.
[8] 闫敬文,屈小波.超小波分析及应用[M].北京:国防工业出版社,2008.
[2] 邢素霞.红外热成像与信号图像处理[M].北京:国防工业出版社,2011.
[3] 许开宇,李双一.基于小波变换的图像融合算法的实现[J].红外技术,2007,29(8):455-458.
[4] 潘泉,张磊,孟晋丽,等.小波滤波方法及应用[M].北京:清华大学出版社,2005.
[5] 谢杰成,张大力,徐文立.小波图像去噪综述[J].中国图像图形学报,2002,7(3):209-218.
[6] 尹士畅,喻松林.基于小波变换和直方图均衡的红外图像增强[J].激光与红外,2013,43(2):265-268.
[7] 李弼程,彭天强,彭波.智能图像处理技术[M].北京:电子工业出版社,2004.
[8] 闫敬文,屈小波.超小波分析及应用[M].北京:国防工业出版社,2008.