Coupling normalized abundance with an improved continuum removal algorithm for quantitative inversion of carbonate minerals using hyperspectral data

Mapping or quantitatively estimating mineral content using remote sensing technology is an active way for monitoring minerals in large or inaccessible areas. Different spectral features of minerals, induced by their ionic composition, can be identified and related to mineral type or abundance. Based on the distinctive spectral absorption around 2.33 mu m induced by the carbonate ion, we propose an improved continuum removal (ICR) algorithm, coupled with normalized abundance, to assess the relationship between continuum removal band depth (CRBD) and carbonate ion abundance. Through experiments using synthetic and real image data, ICR with ratio abundance normalization enhances the linear relationship between CRBD and abundance, resulting in the best performance for abundance retrieval. The synthetic data showed the lowest root mean square error of 0.04, while the lowest mean relative error for real image data reached 6.80 %. Compared it with five other algorithms, coupling normalized carbonate mineral abundance with ICR improves the accuracy of quantitative retrieval of carbonate ion. These results demonstrate that the proposed approach effectively reduces the influence of reflectance differences caused by external factors, providing a more reasonable algorithm to enhance spectral absorb features and quantitatively retrieve mineral abundance. The proposed approach has the potential to extend mineral information extraction even in the absence of sample data, and can be applied in surveys of the Moon and Mars for mineral quantitative analysis.