Viscosity is an important index reflecting paper celluloses degree of polymerization and physical properties. Accurate real time information on viscosity is important for repairing and protecting precious paper materials. However, the traditional papers viscosity analysis method mainly uses chemical means, which takes a long time and will inevitably cause secondary damage to the paper. To solve this problem, hyperspectral remote sensing, with its rich information and real-time, contactless characteristics, is an effective way to obtain the papers viscosity content without damage. First, obtain experimental papers with different aging degrees in the laboratory to measure their viscosity contents, collect hyperspectral data of paper samples, preprocess paper samples hyperspectral data through spectral noise reduction, spectral transformation, and spectral information expansion, establish a spectral database of papers viscosity contents under different aging degrees, and respectively build spectral difference index, ratio index and normalization index under different spectral transformation methods. Correlation analyses were carried out the 12 best spectral indices with the strongest correlation with viscosity were selected. Finally, the selected spectral indices were used as independent variables to build a regression model on the viscosity content. We also selected the spectral index and model that best characterized the change of the papers viscosity content by comparing model accuracy. The results show that: (1) Compared with the original spectrum, the proportion of the highly correlated feature subset of viscosity extracted after spectral transformation processing greatly improved along with the mean and median of the correlation coefficient; (2) The correlation between the spectral information parameters (obtained by spectral information expansion) and viscosity is higher than that of the original spectral segment, and most of the 12 optimal spectral indices extracted have the participation in the expanded information parameters; (3) The correlation between the best spectral index, extracted under different spectral transformation results, and the viscosity content above 0.89, and the three representative spectral indices selected from them effectively reflected the change of papers viscosity at 400~500 mL·g-1; (4) After logarithmic first-order differential treatment of the paper spectrum, the normalized index constructed by spectral integration and spectral absorption depth has the largest correlation with viscosity, reaching -0.917 and the R2 of the model established by this index in the training set and the test set is 0.84 and 0.76 respectively, with MRE and RMSE in the test set as 0.089 and 40.29 mL·g-1, respectively. The research results can provide scientific theory and technical support for the remote sensing inversion of the papers viscosity content, and have important reference significance for the construction of the non-destructive analysis system of paper cultural relics.