摘要
为了解决航空发动机导向叶片数字射线(DR)检测图像信息动态范围大、对比度低、细节信息不明显,缺陷区域难以识别的问题,提出一种改进型限制对比度自适应直方图均衡化(CLAHE)算法。采用CLAHE增强导向叶片DR图像对比度,同时引入基于空间均值滤波器的Gaussian掩模处理,进行DR图像降噪,提取DR图像的低频信息;采用CLAHE增强的图像与提取的DR图像低频信息线性做差,突出DR图像的高频细节信息;与CLAHE增强的图像线性叠加,进一步提高了DR图像的对比度,实现导向叶片DR图像增强。依据图像基本空间分辨率(SRB)、信噪比(SNR)、灰度平均值对DR图像增强效果进行评价。结果表明:改进的CLAHE算法,可以同时将表征SRB的D13双丝线对应的调制深度值从49.17%提高到了56.08%,整体灰度平均值从32400.66增加到了38684.43,02号微小裂纹缺陷的SNR从14.10提升到了15.16。结果显示优化的CLAHE算法,相比自适应直方图均衡化(AHE)等4种经典的航空发动机导向叶片DR图像增强算法,不仅提高了平坦区域对比度,突显了边缘细节信息,而且有效提升了微小缺陷的视觉效果。
In order to solve the problems of large dynamic range,low contrast,inconspicuous detail information,and difficulty in identifying defect areas in the image information detected by digital radiography(DR)of aero-engine guide blades,an improved adaptive histogram equalization algorithm with limited contrast was proposed.Contrast limited adaptive histogram equalization(CLAHE)was used to enhance the contrast of the DR image of the guide vane.Meanwhile,the Gaussian mask processing based on the spatial mean filter was introduced to reduce the image noise and extract the low-frequency information of the DR image.The high-frequency information of DR image was highlighted by difference of CLAHE enhanced image and the low-frequency information of DR image.Furthermore,a linear superimposing of CLAHE enhanced image and highlighted image high frequency information was employed to further improve the contrast of DR image and realize the enhancement of the DR image of the guide vane.In addition,the DR image enhancement effect was evaluated based on the basic spatial resolution of the image(SRB),signal-to-noise ratio(SNR)and gray average.Experimental results showed that the improved CLAHE algorithm can simultaneously increase the modulation depth value characterizing SRB correspondingly to the D13 double-filament wire from 49.17% to 56.08%,and the overall grayscale average value from 32 400.66 to 38 684.43,and the SNR of the No.02 micro crack defect was improved from 14.10 to 15.16.The result showed that the improved CLAHE algorithm not only improved the flat area contrast and highlighted the edge detail information,but also effectively improved visual effect of small defects in comparison with four classic aero-engine guide vane DR image enhancement algorithms such as adaptive histogram equalization(AHE).
作者
冯雄博
陈曦
闵慧娜
吴伟
王树鹏
邬冠华
FENG Xiongbo;CHEN Xi;MIN Huina;WU Wei;WANG Shupeng;WU Guanhua(Key Laboratory of Nondestructive Testing,Ministry of Education,Nanchang Hangkong University,Nanchang 330063,China;Shenyang Liming Aero-Engine Company Limited,Aero Engine Corporation of China,Shenyang 110043,China)
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2022年第7期1425-1436,共12页
Journal of Aerospace Power
基金
国家自然科学基金(62161030,62061033)
基础科研项目(JCKY2019401D001)
南昌航空大学研究生创新专项资金(YC2020-080)。
