Hyperspectral image unmixing method based on subspace clustering constraint, computer readable storage medium and electronic equipment

Abstract

The invention provides a hyperspectral image unmixing method based on subspace clustering constraint, a computer readable storage medium and electronic equipment, solving the problem that the unmixingprecision is not high due to the fact that the complexity of a hyperspectral image ground object and spatial structure characteristics are not fully considered in an existing method. The hyperspectral image unmixing method comprises the following steps: 1) inputting a hyperspectral image Y; 2) embedding a subspace clustering method into a non-negative matrix factorization framework to obtain a joint unified unmixing framework capable of fully mining a data subspace structure; 3) iteratively solving each matrix parameter in the unified framework in the step 2) to respectively obtain an end member coefficient matrix B, an abundance coefficient matrix A and a space self-expression coefficient matrix S; 4) synthesizing an end member by using the end member coefficient matrix B obtained in thestep 3.2) to obtain a demixed end member matrix M; and 5) obtaining an end member matrix M and an abundance coefficient matrix A of the hyperspectral image Y to complete demixing of the hyperspectralimage Y.

Description

technical field [0001] The invention relates to image processing technology, in particular to a hyperspectral image unmixing method based on subspace clustering constraints, a computer-readable storage medium, and electronic equipment, which can be used in environmental monitoring, risk prevention, and mineral exploration. Background technique [0002] With the rapid development of hyperspectral imaging technology in China, hyperspectral images contain more and more spatial and spectral information of ground targets, making them widely used in environmental monitoring, risk prevention and mineral exploration. However, due to the limitations of hyperspectral sensor imaging methods, high spatial resolution and high hyperspectral resolution cannot coexist. Therefore, remote sensing images obtained by hyperspectral satellites generally have low spatial resolution, which also leads to mixed images in the image. generation of pixels. In order to make full use of these hyperspectr...

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Problems solved by technology

[0008] The purpose of the present invention is to solve the problem of low unmixing accuracy caused by the existing methods that do not fully consider the complexity of hyperspectral image features and spatial structure characteristics, and propose a hyperspectral image unmixing method based on subspace clustering constraints, Computer-readable storage media and electronic devices, the method embeds the subspace clustering method into NMF, fully mines the multi-layer subspace structure of the data, and improves the unmixing performance

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