基于小波变换的超声红外热图像处理  

Ultrasonic Infrared Thermal Image Processing Based on Wavelet Transform

作　　者：姬龙鑫 冯辅周 闵庆旭 JI Long-xin;FENG Fu-zhou;MIN Qing-xu(Department of Vehicle Engineering,Academy of Army Armored Forces,Beijing 100072;95944 Unit of the Chinese People's Liberation Army,Wuhan 430300)

机构地区：[1]陆军装甲兵学院车辆工程系,北京100072 [2]中国人民解放军95944部队,武汉430300

出　　处：《长春理工大学学报（自然科学版）》2020年第4期112-116,128,共6页Journal of Changchun University of Science and Technology(Natural Science Edition)

基　　金：国家自然科学基金(51875576)。

摘　　要：超声红外热波检测图像存在对比度低、信噪比不高的问题。为了增强图像视觉效果,提高缺陷检测能力,采用小波变换的方法对红外热图像进行处理。介绍了小波变换和阈值处理的基本原理,先对采集到的红外热图像预处理,再对预处理后的图像进行小波变换获得低频和高频系数,进而采用阈值处理的方法来去除噪声并增强细节系数,最后经过小波重构得到新的红外图像。结果表明,该方法能够有效提高红外图像的对比度和信噪比,为红外图像的缺陷识别奠定基础。Ultrasonic infrared heat wave detection image has the problems of low contrast and low signal-to-noise ratio.In order to enhance the visual effect of the image and improve the defect detection capability,the infrared thermal image is processed by using the wavelet transform method.Introduced the basic principles of wavelet transform and threshold processing.First,the infrared thermal images are pre-processed,then the pre-processed images are wavelet transformed to obtain low-frequency and high-frequency coefficients.Later,use threshold processing to remove noise and enhance detail coefficients.Finally,a new infrared image is obtained by wavelet reconstruction.The results show that this method can effectively improve the contrast and signal-to-noise ratio of infrared images and lay the foundation for defect recognition of infrared images.

关 键 词：超声红外 图像处理 小波变换 阈值去噪 

分 类 号：TG115.8[金属学及工艺—物理冶金]