A hyperspectral image processing method for kaolin information extraction

Abstract

The invention belongs to an information extraction method, and particularly relates to a hyperspecrtal image treatment method for extracting kaolin information. The method comprises the following steps: 1, waveband sampling; 2, judging; 3, computing, namely computing abundance according to the judgment result in the step 2. According to the hyperspecrtal image treatment method, the abundance values of kaolin in different areas within the image range can be accurately calculated by hyperspecrtal image re-sampling, specific waveband extraction, and a series of judgments and computations.

Description

technical field [0001] The invention belongs to an information extraction method, in particular to a hyperspectral image processing method for kaolin information extraction. Background technique [0002] Extracting the abundance of different types of minerals in the image area by processing image information is a commonly used method in the field of exploration. This method does not require staff to go directly to the field for exploration and sampling, and can extract the abundance of different types of minerals. The current kaolin information extraction method of hyperspectral remote sensing images is mainly spectral matching of full band or partial continuous band spectral matching. The specific algorithm includes spectral angle, mixed demodulation filter, etc., because the material composition of the surface is rarely composed of a single mineral However, these methods are easily affected by the spectrum or noise of other ground objects in the process of information ext...

AI Technical Summary

Problems solved by technology

The current kaolin information extraction method of hyperspectral remote sensing images is mainly spectral matching of full band or partial continuous band spectral matching. The specific algorithm includes spectral angle, mixed demodulation filter, etc., because the material composition of the surface is rarely composed of a single mineral Yes, these methods are easily affected by the spectrum or noise of other ground objects in the process of information extraction, and the accuracy of information extraction is relatively low

Secondly, the existing spectrum extraction method has many manual steps, which increases the error of human judgment.

The third is that the hyperspectral data has many bands and a large amount of data. The existing methods take a long time to process, which reduces the speed of data processing and the scale of application.