Jiang Hua, Wu Changdong
School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China.
Laboratory of Intelligent Perception and Smart Operation and Maintenance, Southwest Jiaotong University, Chengdu 610031, China.
Rev Sci Instrum. 2024 Aug 1;95(8). doi: 10.1063/5.0210858.
A substation is important equipment of the power system, and there are many power equipment components in the substation. In order to better detect the working status of power equipment components, it is necessary to preprocess these components. In the actual application, the power equipment images may be noisy due to external environmental interference. Therefore, it should denoise these images in order to improve system detection performance. This paper uses the acquired power equipment images and adds noise intensity of 10, 15, 20, 25, and 30, respectively. Then, the Block-Matching and 3D Filtering (BM3D) method is used to denoise these images. BM3D includes three steps such as block combination, collaborative filtering, and integration, which has strong denoising ability. The experimental results show that the proposed method outperforms other methods in terms of denoising visual effects and evaluation indicators. Especially in terms of preserving details and textures of the denoised image, there is a significant advantage in suppressing strong noise. In summary, the proposed method can achieve encouraging denoising results, which is an effective denoising method for power equipment images.
变电站是电力系统的重要设备,变电站内有许多电力设备部件。为了更好地检测电力设备部件的工作状态,有必要对这些部件进行预处理。在实际应用中,电力设备图像可能会因外部环境干扰而产生噪声。因此,应该对这些图像进行去噪处理,以提高系统检测性能。本文使用采集到的电力设备图像,分别添加强度为10、15、20、25和30的噪声。然后,使用块匹配与三维滤波(BM3D)方法对这些图像进行去噪。BM3D包括块组合、协同滤波和整合三个步骤,具有很强的去噪能力。实验结果表明,该方法在去噪视觉效果和评价指标方面优于其他方法。特别是在保留去噪图像的细节和纹理方面,在抑制强噪声方面具有显著优势。综上所述,该方法能够取得令人满意的去噪效果,是一种有效的电力设备图像去噪方法。