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A Hybrid Fourier-wavelet Denoising Method for Infrared Image of Porcelain Sleeve Cable Terminal Using GSM Model for Wavelet Coefficients

机译:基于小波系数GSM模型的瓷套电缆终端红外图像混合傅里叶小波降噪方法

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In order to remove the white noise of infrared image effectively and improve the accuracy of infrared diagnosis of electrical equipment, a hybrid Fourier-wavelet denoising method is used to process the infrared image of porcelain bushing cable terminal in this paper. The main steps of the proposed method are as follows. The noisy image is first processed in the Fourier domain by using the Wiener filter. Then in wavelet domain, the wavelet coefficients are modeled by using the Gaussians Scale Mixtures model which considers the statistical properties of wavelet coefficients. Finally, the processed wavelet coefficients are used to reconstruct the signal and get the final denoising image. Simulation results indicate that the infrared image denoising effect can be effectively improved by using the denoising method in this paper.
机译:为了有效消除红外图像的白噪声,提高电气设备的红外诊断精度,本文采用混合傅里叶小波去噪方法对瓷套电缆端子的红外图像进行处理。提出的方法的主要步骤如下。首先使用维纳滤波器在傅立叶域中处理噪点图像。然后在小波域中,使用考虑小波系数统计特性的高斯比例混合模型对小波系数建模。最后,处理后的小波系数用于重构信号并获得最终的去噪图像。仿真结果表明,本文采用去噪方法可以有效地提高红外图像的去噪效果。

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