A remote sensing image fusion method and system based on a deep residual neural network

Abstract

The invention discloses a remote sensing image fusion method and system based on a deep residual neural network, and the method comprises the steps of carrying out the downsampling of corresponding multiples on a panchromatic image and a multispectral image, and obtaining a training sample; constructing a deep residual neural network, wherein the network is of a deep convolutional structure, and inputting a panchromatic image and a multispectral image into the deep residual neural network to sequentially pass through outputs obtained by a plurality of convolution modules and adding with the input multispectral image to form a residual structure; using a training sample and a random gradient descent algorithm for training a deep residual neural network, downsampling a multispectral image and a panchromatic image to be fused respectively by corresponding multiples, then inputting the multispectral image and the panchromatic image into the trained deep residual neural network, and obtaining a fused multispectral image with high spatial resolution. According to the invention, the respective key information of the two images can be integrated, and the spatial resolution of the multispectral image is improved.

Description

technical field [0001] The invention belongs to the field of remote sensing image processing, and relates to a method and system for fusing remote sensing images. Background technique [0002] Remote sensing imagery is the main form of information carried by earth observation satellites. It can fully record the electromagnetic wave reflection characteristics of surface objects, so it can be used in important fields such as urban change detection and natural disaster monitoring. Most satellites will obtain multispectral images and panchromatic images of the area at the same time when observing the surface. The multispectral images record the electromagnetic wave reflection characteristics of ground targets in multiple bands, while the panchromatic images only record the ground targets. Electromagnetic wave reflection characteristics in a single band. Although the spectral resolution of multispectral images is ideal, its spatial resolution is not as good as that of panchromat...

AI Technical Summary

Problems solved by technology

Although the spectral resolution of multispectral imagery is ideal, its spatial resolution is not as good as panchromatic imagery due to the physical characteristics of the sensor.

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