Integration of Multisource Spectral Libraries for Spectral Super-Resolution via Benchmark Alignment

Xiaolin Han, Yijie Wei, Wei Wang, Huan Zhang, Weidong Sun

Abstract: Public spectral library that can provide authentic and reliable spectral information has been widely used in various applications, especially in the spectral library based spectral super-resolution. In general, the joint of multisource spectral libraries from different organizations can provide more varied and richer spectral information, but the differences in collection conditions and equipment between multisource spectra may greatly affect their application effectiveness. To cope with this problem, an integration method of multisource spectral libraries via benchmark alignment for spectral super-resolution is proposed. In this method, a pairwise alignment model is designed first, to express the integration procedure of multisource spectral libraries. Second, a statistical intercluster consistency measurement-based benchmark selection strategy for the spectrum pairs crossing two or more spectral libraries is designed, to find out the most suitable spectrum for alignment. Then, a nonnegative background component-based alignment strategy is proposed, to achieve spectral library integration through common background components extracted from the selected benchmark clusters. And finally, a modified spectral super-resolution procedure base on the integrated spectral library is given, to evaluate its effectiveness indirectly. Experimental results with the related spectral super-resolution methods on different datasets demonstrate that, our proposed method can significantly improve the performance of spectral super-resolution in both spatial and spectral domains.

External IDs:dblp:journals/tgrs/HanWWZS25