During the preservation process of ancient calligraphy and paintings, mildew spots are easy to breed mildew stains not only affect the appearances of works, but also cause irreversible and permanent damage to paper cultural relics. In order to provide an intuitive reference for the cleaning of mildew stains on calligraphy and paintings, we proposed a method of stained area extraction and virtual restoration based on hyperspectral imaging. The 244 bands between 450~600 nm significantly different from the stained area spectral curve were selected as the characteristic bands, which were used to extract the stained area by the sequential maximum angle convex cone and gray-scale segmentation algorithm. Next, the hyperspectral image was transformed by the principal component analysis. The first three principal components were selected to synthesize a pseudo color image, which was restored virtually by typical algorithm of Criminisi. Then, inverse principal component transformation was performed on the restored image to complete the virtual restoration of the hyperspectral image. Taking a painting by Ni Tian as an example, we found that the restored stained area was better integrated with the painting body, the boundary was naturally smooth, and the root mean square error value generally became smaller. The research results could provide an intuitive restoration basis for the cleaning of mildew stains on calligraphy and paintings, and have strong practicability.