CAJ | 학술논문

为了从强白噪声干扰的红外热像中提取真实的绝缘子盘面温度场信息,提出一种基于MAP估计的复小波域局部自适应去噪方法.首次证实了绝缘子红外热像双树复小波变换(DT-CWT)系数服从拉普拉斯分布,并对不同滤波器组采用各自最精细分解层子带系数估计噪声方差,利用待估计点圆形邻域系数估计信号方差,且随分辨率变化调整圆形邻域半径,使得MAP估计的无噪声系数更为准确,提高了去噪图像质量.实验结果表明,该方法比传统的Wiener滤波法、基于离散小波变换和DT-CWT的贝叶斯阈值去噪方法具有更高的信噪比,在有效去除图像噪声的同时,图像细节信息保留更完好.
위료종강백조성간우적홍외열상중제취진실적절연자반면온도장신식,제출일충기우MAP고계적복소파역국부자괄응거조방법.수차증실료절연자홍외열상쌍수복소파변환(DT-CWT)계수복종랍보랍사분포,병대불동려파기조채용각자최정세분해층자대계수고계조성방차,이용대고계점원형린역계수고계신호방차,차수분변솔변화조정원형린역반경,사득MAP고계적무조성계수경위준학,제고료거조도상질량.실험결과표명,해방법비전통적Wiener려파법、기우리산소파변환화DT-CWT적패협사역치거조방법구유경고적신조비,재유효거제도상조성적동시,도상세절신식보류경완호.
In order to gain the real temperature distribution of insulator surface from infrared thermal image that is strongly interfered by white-noise, a complex wavelet-domain local adaptive denoising method based on maximum a posteriori (MAP) estimation is developed. It is confirmed for the first time that the dual tree complex wavelet transform (DT-CWT) coefficients of insulator infrared thermal image obey Laplacian distribution. The authors utilize the finest scaling sub-band coefficients of different filter banks to estimate their respective noise variances, and compute the signal variance of the coefficient using neighboring coefficients within a circular window whose radius varies with resolution, so noise-free coefficients are more accurately estimated by MAP estimation and the quality of the denoised image is improved. Experimental results demonstrate that the proposed method gets higher signal-to-noise rate (SNR), de-noises more effectively and preserves more detailed information of the original image than traditional Wiener filtering method, the adaptive Bayesian threshold methods based on discrete wavelet transform and DT-CWT.