The writing on the surface of artifacts provides key information for understanding history, and the exploration of it becomes an important part of artifact conservation. Combining manifold learning and spectral unmixing, we propose a new method to enhance the writing on the surface of artifacts. Firstly, isometric feature mapping based on manifold learning was used to reduce the nonlinear dimension of the preprocessed hyperspectral images, and a gray image with the most abundant information was obtained. Secondly, the spectral characteristics of text and background were analyzed, and the multilayer nonnegative matrix decomposition method was used to obtain the handwriting abundance map. Then the gray image and the abundance map of the handwriting were weighted together to obtain the handwriting enhancement image; the handwriting fusion image was obtained by HSV fusion of the handwriting enhancement image and true color image. Finally, in order to better identify the text, it was cropped on the handwriting enhancement image and morphological transformation was performed to obtain the handwriting extraction map. The hyperspectral image of a faded text in Cave 38 of Yungang Grottoes was taken as an example, the results showing that the proposed method could effectively enhance the text on the surface of cultural relics and its effect was better than those of other enhancement methods.