Hyperspectral image compressed sensing reconstruction method based on space-spectrum combined multi-hypothesis prediction

Abstract

The invention provides a hyperspectral image compression sensing reconstruction method based on space-spectrum combined multi-hypothesis prediction, belonging to the technical field of image compression, comprising the following steps: acquiring hyperspectral images by a hyperspectral imager; and reconstructing the hyperspectral images. As the method adopts the spatial correlation and the inter-spectrum correlation to predict the hyperspectral image, the prediction accuracy is improved compared with the existing prediction technology; As an iterative mode is adopted to realize the residual error reconstruction of the hyperspectral image, the defect of low precision of a reconstructed image, the spatial correlation and inter-spectrum correlation of hyperspectral images are described more fully by establishing a multi-hypothesis prediction model, which solves the problem that the spatial and inter-spectrum characteristics are not sufficiently utilized by the existing hyperspectral imagecompression and perceptual reconstruction algorithms.

Description

technical field [0001] The invention belongs to the technical field of image compression, and in particular relates to a hyperspectral image compression sensing reconstruction method based on space-spectrum joint multi-hypothesis prediction. 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] Due to the high spatial and spectral resolutio...

AI Technical Summary

Problems solved by technology

To sum up, the main problem of the existing technology is that the spatial and spectral characteristics of the hyperspectral image are not fully utilized, and the reconstruction performance cannot be further improved.

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