Hyperspectral remote sensing image dimensionality reduction method based on conformal geometric algebra

Abstract

The invention discloses a hyperspectral remote sensing image dimensionality reduction method based on conformal geometric algebra. The method includes the steps of firstly, collecting hyperspectral data, preprocessing the same, and the like; secondly, performing information expression on the hyperspectral data under a conformal geometric algebra space, and building the mapping relations among data of different spaces; thirdly, building a hyperspectral image feature distance operation operator; fourthly, building the expression method of distance measurement on the basis of the conformal geometric algebra; fifthly, calculating the distances of different wave bands, and k adjacent wave bands of each wave band; sixthly, using a Floyd shortest path calculation algorithm to calculate the shortest distance among the wave bands, and using the shortest distance as the matrix for dimensionality reduction; seventhly, using a PCA algorithm to calculate b feature values of the distance matrix, using the b feature values as the mapping coordinate systems, and taking the wave band data described by the coordinate systems as the to-be-selected wave band data. By the method, the hyperspectral remote sensing image feature extracting effect can be increased, and data information loss caused by the existing hyperspectral image data dimensionality reduction methods can be reduced.

Description

technical field [0001] The invention belongs to the technical field of hyperspectral remote sensing image processing, and in particular relates to a hyperspectral remote sensing image dimensionality reduction method based on conformal geometric algebra. Background technique [0002] In recent years, hyperspectral remote sensing has become a new research hotspot in the field of remote sensing technology. Compared with conventional remote sensing, hyperspectral remote sensing can use the nanoscale spectral resolution of imaging spectrometers to obtain a large amount of very narrow and spectrally continuous image data, realizing the spatial Synchronous acquisition of , radiation, and spectral information; hyperspectral images retain high spatial resolution while greatly improving spectral resolution, which makes it possible to describe the details of similar objects or identify different types of objects Therefore, it has been widely used in land use change and cover, disaster ...

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Problems solved by technology

[0005] Purpose of the invention: In view of the problems and deficiencies in the above-mentioned prior art, the purpose of the present invention is to provide a hyperspectral remote sensing image dimensionality reduction method based on conformal geometric algebra to solve the problem of poor selection of hyperspectral remote sensing bands and large information loss And other issues

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