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Ultraviolet Image Processing Method in Corona Detection

机译:电晕检测中的紫外图像处理方法

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Ultraviolet image detection technology is the first choice of the corona detection in power system, which could fulfill an all-weather reliable detection on corona. However, the solar-blind ultraviolet signal issued by corona discharge is relatively weak, and the quality of ultraviolet image is seriously affected by the noise from the detection system. The noise characteristics of the ultraviolet image that is detected by the corona has been analyzed in this paper, one kind of image denoising methods based on mathematics morphology and independence component analysis is put forward, and is applied to the corona and solar-blind ultraviolet image processing method. The method which improves the SNR of images, enhances the goal and weakens the noise is proved by experiments.
机译:紫外图像检测技术是电力系统电晕检测的首选,这可能符合电晕的全天候可靠检测。然而,由电晕放电发出的太阳盲紫外线信号相对较弱,紫外线图像的质量受到来自检测系统的噪声的严重影响。本文已经分析了由电晕检测的紫外图像的噪声特性,提出了一种基于数学形态和独立分析分析的一种图像去噪方法,并应用于电晕和太阳盲紫外图像处理方法。改善图像SNR的方法,增强了目标并削弱了通过实验证明了噪声。

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