Division of Industrial Informatics, Silesian University of Technology, Katowice, Poland.
Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland.
PLoS One. 2021 Jun 28;16(6):e0253117. doi: 10.1371/journal.pone.0253117. eCollection 2021.
The substantial improvement in the efficiency of switching filters, intended for the removal of impulsive noise within color images is described. Numerous noisy pixel detection and replacement techniques are evaluated, where the filtering performance for color images and subsequent results are assessed using statistical reasoning. Denoising efficiency for the applied detection and interpolation techniques are assessed when the location of corrupted pixels are identified by noisy pixel detection algorithms and also in the scenario when they are already known. The results show that improvement in objective quality measures can be achieved by using more robust detection techniques, combined with novel methods of corrupted pixel restoration. A significant increase in the image denoising performance is achieved for both pixel detection and interpolation, surpassing current filtering methods especially via the application of a convolutional network. The interpolation techniques used in the image inpainting methods also significantly increased the efficiency of impulsive noise removal.
描述了一种用于去除彩色图像中脉冲噪声的开关滤波器的效率的显著提高。评估了许多噪声像素检测和替换技术，使用统计推理评估了彩色图像的滤波性能和后续结果。当使用噪声像素检测算法识别损坏像素的位置时，以及在已知损坏像素的位置时，评估应用的检测和插值技术的去噪效率。结果表明，通过使用更鲁棒的检测技术，结合受损像素恢复的新方法，可以提高客观质量度量。在像素检测和插值方面，图像去噪性能都得到了显著提高，尤其是通过应用卷积网络，超过了当前的滤波方法。在图像修复方法中使用的插值技术也显著提高了脉冲噪声去除的效率。
