A fast compressed sensing reconstruction method for hyperspectral images based on particle swarm optimization

A technology of compressed sensing reconstruction and hyperspectral image, applied in image coding, image data processing, instruments, etc., can solve the problems of high computational complexity and inability to achieve rapid reconstruction of hyperspectral images.
CN109087367AActive Publication Date: 2018-12-25XIAN AERONAUTICAL UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
XIAN AERONAUTICAL UNIV
Publication Date
2018-12-25

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Abstract

The invention discloses a fast compression sensing reconstruction method of hyperspectral image based on particle swarm optimization, the invention relates to the technical field of image compressionprocessing, the invention discloses a fast compression sensing reconstruction method of hyperspectral image based on particle swarm optimization, which mainly solves the problem of high computationalcomplexity of the existing orthogonal matching pursuit reconstruction algorithm, the key of the technology is to use the idea of Particle Swarm Optimization, the matching process of the orthogonal matching pursuit algorithm is optimized, Using particles to represent atoms in redundant dictionaries, Based on the fast searching ability of particle swarm optimization (PSO), the optimal atom for sparse representation of hyperspectral images is found, and then the residual updating process of orthogonal matching pursuit (OMPR) reconstruction algorithm is accelerated by Hermitian inversion. The method of the invention can improve the calculation efficiency under the condition of maintaining the reconstruction accuracy.
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Description

technical field

[0001] The present invention relates to the technical field of image compression processing, in particular to a hyperspectral image fast compression sensing reconstruction method based on particle swarm optimization. Background technique

[0002] Hyperspectral images not only contain the spatial distribution information of the observed target, but also each pixel in the image has dozens or even hundreds of narrow bands of rich spectral information, which has the property of "integrating graphs and spectra into one". Since hyperspectral images can combine spectral features reflecting material properties with image information presenting material geometric space information, it has greatly improved the ability of human beings to recognize the objective world, and has been widely used in remote sensing, military, agriculture, medicine and other fields. It is proved to have great application value.

[0003] If spatial sampling is performed on each band image of ...

Claims

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