Principal component analysis-based imaging spectral image super resolution restoration method

Abstract

The invention discloses a principal component analysis-based imaging spectral image super resolution restoration method. The method includes the steps of principal component analysis, gray mapping and MAP-based first principal component super resolution restoration and all-band super resolution restoration of an imaging spectral image. According to the principal component analysis-based imaging spectral image super resolution restoration method, the effective information of the imaging spectral image is concentrated on a first principal component through PCA transform, with the super resolution restoration of the first principal component simply realized, the spatial resolution of all bands can be improved, and therefore, the amount of computation is small; mapping from panchromatic image high-frequency information to a first principal component image can be realized through establishing a gray mapping model and based on the correlation between the first principal component and a panchromatic image after the PCA transform, and the quality of a reconstructed high-frequency information can be further improved through MAP constrained optimization; and therefore, high-frequency information of the panchromatic image can be fully utilized, and the introduction of wrong information can be avoided, and the quality of a reconstructed high-resolution image can be ensured, and the problem of spectrum distortion caused by independent operation of each band can be effectively solved.

Description

technical field [0001] The invention relates to a method for super-resolution restoration of imaging spectral images, in particular to a method for super-resolution restoration of imaging spectral images based on principal component analysis (Principal Component Analysis, PCA). Background technique [0002] Imaging spectroscopy technology is a new remote sensing technology that developed rapidly in the 1980s. It obtains the radiation information of surface features in dozens or even hundreds of bands at the same time with ultra-high spectral resolution at the nanometer scale, so it can acquire ground features While collecting the spatial information of the target, it detects its internal physical characteristics and composition. Imaging spectroscopy technology is widely used in resource exploration, geological exploration, disaster relief and other fields. [0003] Spatial resolution and spectral resolution are two important parameters to measure the quality of imaging spec...

AI Technical Summary

Problems solved by technology

[0008] The existing technology does not fully consider the ability to maintain spectral dimension information in the super-resolution restoration process for the super-resolution restoration of imaging spectral images, resulting in the reconstruction of high-resolution images often with certain spectral distortions

In addition, there are many bands of hyperspectral images, and the super-resolution restoration of all bands is often unbearable due to the huge amount of computation.

Images