## 3 Materials and Methods
### Evaluation of the Face Image Inpainting Results  
The quality of the images in this study was evaluated from both subjective and objective perspectives. First, we used SSIM and PSNR as objective evaluation tools [70]. PSNR quantified image fidelity by calculating the pixel-level error between the original image and the restored image from a mathematical perspective. SSIM, on the other hand, evaluated the perceived quality of the image based on the human visual system's perception characteristics, considering the structural information of the image. The combined application of these two methods provided a solid quantitative foundation for the comprehensive evaluation of image performance.  
Secondly, this study employed the Absolute Category Rating (ACR) as a subjective evaluation method, which is suitable for the subjective assessment of the overall quality of static images [37]. Subjective measurement is the most reliable method to determine the actual image quality, as humans are the ultimate recipients in most applications. We prepared the restored images and ensured they are displayed at the same resolution and on the same monitors. To ensure the broadness and objectivity of the evaluation results, the evaluators of the questionnaire survey were divided into two groups: one group consisted of experts with relevant knowledge and experience, and the other group consisted of students majoring in cultural heritage conservation. Evaluators scored the images based on two aspects: texture and structure, using a discrete five-level scoring scale: Poor (1), Fair (2), Medium (3), Good (4), Excellent (5). Each evaluator scored the images independently, without being influenced by other evaluators. We collected the scores from all evaluators and calculated the average scores and standard deviations for texture and structure. By analyzing the scoring data, we could assess the restoration effectiveness and provide further improvement suggestions based on the evaluators' feedback.  
Finally, this study used Pearson correlation analysis to show the degree of correlation between subjective and objective indicators, thereby verifying the consistency and reliability between subjective and objective evaluations. The Pearson correlation coefficient is a common parametric test method used to measure the linear correlation between two  
Figure 7: Algorithm architecture diagram.  
variables [71]. The value of the Pearson correlation coefficient ranges from \(-1\) to +1, where the absolute value closer to 1 indicates a stronger correlation between the variables. The sign of the coefficient indicates the type of correlation: a positive coefficient (positive sign) indicates that when one variable increases, the other variable also increases, whereas a negative coefficient (negative sign) indicates the opposite. The specific values were calculated using SPSS software 29.0.  
The aim of this study was to provide a comprehensive evaluation of the restored facial images of the Tang Dynasty terracotta figurines through this diversified evaluation method, providing a scientific and thorough reference for subsequent protection and restoration work.