Target detection method and system based on local-preserving projection algorithm based on space-spectrum combination

Abstract

The invention discloses a target detection method and system based on a space-spectrum combination local preservation projection algorithm. The method adds an endmember extraction step in the LPP algorithm, indirectly measures the adjacency relationship between pixels by calculating the similarity between the pixel and the image endmember, reduces the influence of spectral fluctuations on the feature similarity, and improves the adjacency weight Matrix construction accuracy; on this basis, by further increasing the spatial domain adjacency weight matrix of the pixel, the effective sample points in each direction of the pixel can fully play their roles, so that the dimensionality reduction data can more accurately reflect the original hyperspectral image. The essential structure can improve the detection accuracy of the target detection results.

Description

technical field [0001] The invention relates to the technical field of remote sensing image data processing and application, in particular to a target detection method and system based on a local-preserving projection algorithm based on space-spectrum combination. Background technique [0002] Dimensionality reduction of hyperspectral data is the first step in the processing and application of remote sensing image data, and it is also an important means and basis for people to obtain remote sensing information. At present, hyperspectral image dimensionality reduction methods are mainly divided into two categories: linear dimensionality reduction and nonlinear dimensionality reduction. Typical representatives of linear dimensionality reduction methods include principal component analysis (Principal Component Analysis, PCA) method and independent component analysis algorithm. The low-dimensional features obtained by these methods can better preserve the global characteristics...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a target detection method and system based on a space-spectrum combination local preservation projection algorithm, to solve the problem that the existing hyperspectral image dimensionality reduction method mainly uses the spectral information of the hyperspectral image in the dimensionality reduction process, ignoring other Spatial distribution information, which leads to the problem of low target detection accuracy

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