Jingdezhen Ceramic University, Jingdezhen, Jiangxi Province, China.
Hangzhou City University, Hangzhou, Zhejiang Province, China.
PLoS One. 2024 Aug 29;19(8):e0305118. doi: 10.1371/journal.pone.0305118. eCollection 2024.
In order to solve the problem of image quality and morphological characteristics of primary underglaze brown decorative pattern extraction, this paper proposes a method of primary underglaze brown decorative pattern extraction based on the coupling of single scale gamma correction and gray sharpening. The single-scale gamma correction is combined with the gray sharpening method. The single-scale gamma correction improves the contrast and brightness of the image by nonlinear transformation, but may lead to the loss of image detail. Gray sharpening can enhance the high frequency component and improve the clarity of the image, but it will introduce noise. Combining these two technologies can compensate for their shortcomings. The experimental results show that this method can improve the efficiency of last element underglaze brown decorative pattern extraction by enhancing the image retention detail and reducing the influence of noise. The experimental results showed that F1Score, Miou(%), Recall, Precision and Accuracy(%) were 0.92745, 0.82253, 0.97942, 0.92458 and 0.92745, respectively.
为了解决原始釉下棕彩装饰图案提取中的图像质量和形态特征问题，本文提出了一种基于单尺度伽马校正和灰度锐化耦合的原始釉下棕彩装饰图案提取方法。单尺度伽马校正与灰度锐化方法相结合。单尺度伽马校正通过非线性变换来提高图像的对比度和亮度，但可能导致图像细节的丢失。灰度锐化可以增强图像的高频分量，提高图像的清晰度，但会引入噪声。将这两种技术结合起来可以弥补彼此的不足。实验结果表明，该方法可以通过增强图像保留细节和减少噪声的影响，提高最后元素釉下棕彩装饰图案提取的效率。实验结果表明，F1Score、Miou(%)、Recall、Precision 和 Accuracy(%)分别为 0.92745、0.82253、0.97942、0.92458 和 0.92745。
