Method for automatically identifying rock minerals based on spectral information

Abstract

The invention belongs to the field of hyperspectral remote sensing application, and particularly discloses a method for automatically identifying rock minerals based on spectral information. The method comprises the following steps: scanning rock minerals to be classified by using a hyperspectral scanner to obtain mineral spectral data; storing the obtained data in a database to be detected; extracting a part of data from the database; identifying mineral species information corresponding to the extracted spectral data according to features of the mineral spectral data by using manual interpretation, and storing the extracted spectral data and the corresponding mineral species information as a learning sample library; establishing an artificial intelligence learning system, and performinglearning and training by using the learning sample library; and detecting the spectral data in the database to be detected by using the artificial intelligence learning system after training and learning optimization to identify the mineral species information; and storing an identification result in an identification result database. By adoption of the method, the human resource consumption can be reduced, the working automation degree is improved, the spectral scanning data processing efficiency is improved, and the economic efficiency is improved.

Description

technical field [0001] The invention belongs to the application field of hyperspectral remote sensing, and specifically discloses a method for automatically identifying rock minerals based on spectral information. Background technique [0002] Rock minerals have unique diagnostic characteristic absorption bands due to their unique chemical composition and physical structure. These characteristic bands have relatively stable wavelength positions and unique waveforms, and their characteristics include spectral absorption peak positions and absorption peak depths. , Absorption peak width and other characteristic parameters, through these characteristics or their combination, the identification of minerals can be realized. The traditional identification of minerals based on spectral information is usually manual identification, which is slow, inefficient, and labor-intensive. Although software such as ENVI currently has some methods for automatically identifying substances base...

AI Technical Summary

Problems solved by technology

The traditional identification of minerals based on spectral information is usually manual identification, which is slow, inefficient, and labor-intensive.

Although software such as ENVI currently has some methods for automatically identifying substances based on spectral information, the identification accuracy is not high, the efficiency is low, and it is difficult to automatically process a large amount of data

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