Hyperspectral image demixing method and system based on abundance significance analysis

A hyperspectral image and hyperspectral remote sensing technology, which is applied in the field of hybrid pixel decomposition of hyperspectral remote sensing images, can solve the problems of lack of unmixed abundance, sparse real abundance of pixels, and algorithm errors, so as to improve accuracy and improve The effect of unmixing precision

Active Publication Date: 2015-03-25
WUHAN UNIV
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[0028] Although the mixed pixel decomposition method based on sparse regression emphasizes the sparsity of understanding, due to the interference of noise, the strong coherence of end-member spectra in the spectral library, and algorithm errors, the un

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  • Hyperspectral image demixing method and system based on abundance significance analysis
  • Hyperspectral image demixing method and system based on abundance significance analysis

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[0064] In order to better understand the technical solutions of the present invention, the specific implementation manners are described below in conjunction with the examples and accompanying drawings.

[0065] When the technical scheme of the method of the present invention is specifically implemented, those skilled in the art can use computer software technology to realize automatic operation. A kind of hyperspectral remote sensing image mixed pixel decomposition method based on abundance saliency analysis proposed by the present invention, the flow chart is as follows figure 1 , 2 shown, where figure 1 is a flow chart of establishing an endmember spectral library of an image to be processed based on an existing endmember spectral library, figure 2 Flowchart for building an endmember spectral library for extracting endmembers from images to be processed. The method embodiment of the present invention specifically comprises the following steps:

[0066] Step 1. Establis...

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Abstract

The invention provides a hyperspectral image demixing method and system based on abundance significance analysis. The method comprises the steps of establishing an end member spectrum bank of a hyperspectral remote sensing image to be processed; conducting preliminary mixed pixel decomposition on each pixel with the sparse regression-based mixed pixel decomposition method, ranking abundance values in a descending order, conducting significance analysis on the abundance sequence obtained through ranking to obtain the critical value of significance abundance, and then judging a sparse representation end member subset constituting the pixel according to a preset significance abundance threshold value; finally, conducting mixed pixel decomposition again with the abundance restraint type least square method, and taking the result as the final mixed pixel decomposition result. By the adoption of the method and system, a more sparse and accurate pixel representation end member subset can be obtained, hyperspectral remote sensing image mixed pixel decomposition precision can be improved, and the method and system have significant application value in high-precision terrain classification and ground target detection and recognition based on hyperspectral remote sensing images.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and relates to a hyperspectral remote sensing image mixed pixel decomposition method based on abundance significance analysis. Background technique [0002] Hyperspectral remote sensing images have high spectral resolution and can analyze the material composition of ground objects in a more detailed and precise manner. Therefore, they have attracted great attention from scholars at home and abroad and have been widely used in ground object classification, anomaly detection, and target recognition. . However, the spatial resolution of hyperspectral images is generally low, and a pixel usually contains the spectra of multiple ground objects, and these pixels are called mixed pixels. The ubiquity of mixed pixels greatly hinders the application of hyperspectral remote sensing images. The mixed pixel decomposition of hyperspectral remote sensing images is one of the core issu...

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Application Information

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IPC IPC(8): G06K9/62G06T7/00
CPCG06T7/70G06T2207/10032G06F18/24
Inventor 邵振峰王毓乾张磊周维勋张邻晶
Owner WUHAN UNIV
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