Abstract
Aiming at the problem that the accuracy of the results obtained by traditional methods is low, the spectral detection in soil pollution component detection method is used to design multicolor heavy metal image identification. The soil reflectance spectra were measured using an ASD Fieldspec FR spectrometer to obtain soil heavy metal spectral data. Spectral absorption bands, spectral transformations and combinations, correlation analysis, and curve fitting operations are used to process and analyze spectral data. Among them, spectral transformation and combination are used to decompose overlapping mixed spectra by first-order and second-order differential operations, to expand the spectral characteristics of heavy metals in different soils, and to extract high-quality spectral data of soil heavy metals. The spectral data is combined with Newton’s classic rainbow spectrum to obtain different heavy metal spectral colors. Based on this, multicolor image identification of soil pollution components is designed. The results show that the multicolor heavy metal image identification can be used to design the multicolor heavy metal image identification by the spectral detection in the soil pollution component detection method, and it can play the pollution warning role.
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The research results of the 2019 education science planning project of the 13th five year plan of Shanxi Education Science Application Research of Shanxi traditional art resources in art education of colleges and universities (subject No.: GH-19131).
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This article is part of the Topical Collection on Geological Modeling and Geospatial Data Analysis
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Han, T. Design and application of multicolor image identification in soil pollution component detection. Arab J Geosci 13, 905 (2020). https://doi.org/10.1007/s12517-020-05873-y
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DOI: https://doi.org/10.1007/s12517-020-05873-y