Hyperspectral and panchromatic image fusion method based on cascade network

Abstract

The invention provides a hyperspectral and panchromatic image fusion method based on a cascade network, and belongs to the technical field of image processing, and the method comprises the following steps: integrating a detail injection method and a spectral unmixing model into a cascade convolutional neural network, constructing an end-to-end network model, estimating the abundance of the pixels of a hyperspectral image, and reconstructing a hyperspectral image with high spatial resolution. According to the method, the panchromatic image is introduced and fused with the hyperspectral image, so that the spatial resolution of the hyperspectral image can be improved, and meanwhile, the spectral distortion phenomenon of the fused image is reduced. By establishing a hyperspectral image fusion model based on the cascade convolutional network, a detail injection method and a spectral unmixing model are integrated into an end-to-end network structure, and the space and spectral information of an input multi-source image can be effectively extracted to generate the abundance value of each end member of a high-resolution image.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a hyperspectral and panchromatic image fusion method based on a cascade network. Background technique [0002] Hyperspectral imaging is one of the most important detection methods in the field of remote sensing. It can obtain the spectral information of various ground objects while obtaining the distribution information of the surface, so as to realize the combination of image and spectral information. The most prominent features of hyperspectral images are their fine spectral resolution and rich spectral information, which can effectively detect diagnostic features that are different from traditional multispectral or human eyes, thus significantly improving human understanding of the world. cognitive ability. However, the improvement of spectral resolution of hyperspectral images is at the expense of spatial resolution. spatial resolution. [0003] Traditional hypers...

AI Technical Summary

Problems solved by technology

However, the existing CNN-based image fusion method lacks the accurate extraction of spectral information of hyperspectral images, does not consider the problem of spectral mixing, and cannot well solve the spectral distortion phenomenon existing in images.

Images