Typical Mineral Abundance Estimation of Chang’e-3 Yutu Rover with Hyperspectral Data Based on Diffusion Autoencoder Unmixing Model

Hyperspectral sensors carried by lunar rovers or satellites can effectively invert the mineral abundance of the lunar surface. Due to special environment of the lunar surface and small number of samples, it is a challenge to analyze typical minerals on the lunar surface using hyperspectral images. In this paper, a spectral-spatial diffusion autoencoder unmixing model (SSDiffAU) is proposed for mineral mapping. This is the first time the diffusion model is invoked in the unmixing field. The 3D-CNN is utilized as an encoder to represent deep spectral-spatial information. Additionally, the diffusion model is used to obtain high quality abundance maps, and then the endmember matrix is obtained by the decoder. Finally, the performance of the proposed algorithm was verified using popular unmixing datasets. The hyperspectral data acquired by Chang'e-3 Yutu rover are unmixed to estimate typical mineral spectra and their abundance.