ZY-1 02D Hyperspectral Imagery Super-Resolution via Endmember Matrix Constraint Unmixing

Abstract

This paper proposes an endmember matrix constraint unmixing method for ZY-1 02D hyperspectral imagery (HSI) super-resolution reconstruction (SRR) to overcome the low resolution of ZY-1 02D HSI. The proposed method combines spectral unmixing and adds novel smoothing constraints to traditional non-negative matrix factorization to improve details and preserve the spectral information of traditional SRR methods. The full utilization of the endmember spectral matrix and endmember abundance matrix of HSI and multispectral imagery (MSI) reconstructs the high spatial resolution and high spectral fidelity HSI. Furthermore, given the ZY-1 02D HSI infrared bands are seriously corrupted by noise, the influence of denoising on the SRR accuracy is also discussed. Experiments show that the proposed method restores spatial details and spectral information and is robust for noise, preserving more spectral information. Therefore, the proposed method is a ZY-1 02D HSI SRR method with high spatial resolution and high spectral fidelity, which improves the spatial resolution while simultaneously solving spectral mixing and provides the possibility for the data further expansion.