摘要
针对电力设备红外灰度图像的细节不清、边缘模糊等缺陷,提出一种基于非下采样剪切波变换(NSST)的电力设备红外图像处理方法。首先,利用NSST对原始的电力设备红外图像进行变换,将数据从空间域转换到频域。然后,对高频系数使用鲸鱼自适应阈值去噪算法去噪,同时增强了高频系数中的细节和边缘部分;对低频系数采用改进的结合均值和方差的大津(MVOtsu)算法将低频分量分成前景部分和后景部分,并分别采用伽马校正算法和直方图均衡化算法进行增强。最后,通过NSST的逆变换得到增强后的图像。所提算法与其他算法的对比结果表明,所提算法能更好地突出电力设备红外图像的细节信息,增强了图片对比度,达到了更好的视觉效果。
Aiming at the defects of unclear details and blurred edges of infrared gray images of power equipment,a processing method for infrared images of power equipment based on non-subsampled shearlet transform(NSST)is proposed in this paper.Firstly,NSST is used to transform the original infrared image of power equipment,and the data is transformed from the spatial domain to the frequency domain.Then,the high-frequency coefficients are denoised by using the denoising algorithm based on whale adaptive threshold.The details and edges of the high-frequency coefficients are enhanced at the same time.For the low-frequency coefficients,the improved mean and variation Otsu(MVOtsu)algorithm is adopted to divide the low-frequency components into foreground and background components,and the gamma correction algorithm and histogram equalization algorithm are respectively adopted to enhance the foreground and background components.Finally,the enhanced image is obtained by the inverse transformation of NSST.The comparison results between the proposed algorithm and other algorithms show that the proposed algorithm can better highlight the details of the infrared image of power equipment,enhance the image contrast,and achieve better visual effect.
作者
王爱平
粟莲
杨海运
王昕
WANG Ai-ping;SU Lian;YANG Hai-yun;WANG Xin(Bazhong Power Supply Company,State Grid Sichuan Electric Power Corporation,Bazhong 636000,China;Center of Electrical and Electronic Technology,Shanghai Jiao Tong University,Shanghai 200240,China)
出处
《控制工程》
CSCD
北大核心
2022年第12期2293-2299,共7页
Control Engineering of China
基金
国家自然科学基金资助项目(61673268)。
