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Abstract The color restoration of Tang and Song Dynasties paintings holds significant importance for the research and presentation of traditional Chinese culture. However, current color restoration methods have their shortcomings. Restoration methods guided by subjective knowledge are relatively inefficient and difficult to reverse, while methods guided by objective data produce unstable results and make it difficult to evaluate the finished products. Under existing technical conditions, achieving absolutely perfect restoration remains impossible. However, based on long-term research and practice, this study suggests that a pattern governing Tang and Song Dynasties painting color restoration can be systematically analyzed and traced.
For this research, the primary visual material used is a high-resolution photographic image of Luohan Laundering. This serves as the unretouched reference image. The corresponding restored digital image from A Comprehensive Collection of Ancient Chinese Paintings is used as the restored version. This study proposes the following hypotheses. Hypothesis 1: The color difference between unrestored and restored paintings is a constant numerical value. Hypothesis 2: If the color difference is not a constant, then at the very least, there exists a statistical correlation between corresponding color values in unrestored and restored paintings. This correlation may vary depending on the type of color and could potentially be described using a mathematical model. Hypothesis 3: For a given color, the numerical values of corresponding color regions in unrestored and restored paintings exhibit a systematic correlation, and the restored color can be directly computed.
Through empirical research, this study first refuted Hypothesis 1. The results of color difference calculations indicated significant fluctuations in the color difference at corresponding positions before and after restoration, rather than a constant value. Second, the results of the correlation analysis demonstrated a statistically significant relationship between the unrestored and restored colors. However, regression analysis revealed that no statistically viable mathematical model could be constructed. Consequently, it is not possible to derive the restored color values directly through computational methods based on the unrestored colors. Therefore, Hypothesis 2 was only partially supported. The research speculates that this outcome may be due to differences in the chemical properties of various pigments. Even under identical preservation conditions, the degree of fading and discoloration may vary across different pigment types, resulting in considerable fluctuations in color differences. To further explore these findings, this study proceeded to test Hypothesis 3, which posited that“the color values of the same color at corresponding positions in the unrestored and restored paintings exhibit a correlation, and the restored color can be directly obtained through computation”. The results, however, refuted Hypothesis 3. Even when analyzing a single-color category, no statistically viable regression relationship could be established between the unrestored and restored versions of the painting. This finding demonstrates that the idea of deriving a mathematical relationship for color restoration based solely on comparing pre- and post-restoration color values is currently infeasible. While the data obtained in this study may provide insights for refining existing restoration methods, practical applications will still need to rely on well-established restoration techniques.
The process of color restoration is inherently complex, encompassing chemical, historical, and artistic knowledge that may not be easily expressed through a simple mathematical model. Using Luohan Laundering as a case study, this research explores the mathematical relationship between colors in unrestored and restored paintings from the Tang and Song Dynasties through an empirical approach. The findings reveal significant correlations between corresponding color values before and after restoration in both the RGB and Lab color models. However, due to the inconsistency of color shifts, constructing a fully reliable mathematical model remains a challenge. The conclusions and findings of this study could contribute to the refinement of data-driven restoration methods, aiding in the development of restoration databases and algorithmic models to enhance the precision and efficiency of color restoration.
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Published: 25 July 2025
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