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Remote sensing image fusion method based on deep convolutional neural network

A remote sensing image fusion and neural network technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as spectral distortion and spatial information loss, and achieve clear structure, high spatial resolution, and rich spectral information Effect

Pending Publication Date: 2021-11-23
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

Traditional image fusion methods usually cause loss of spatial information and spectral distortion

Method used

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  • Remote sensing image fusion method based on deep convolutional neural network
  • Remote sensing image fusion method based on deep convolutional neural network
  • Remote sensing image fusion method based on deep convolutional neural network

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Embodiment Construction

[0030] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0031] like figure 1 As shown, the present invention discloses a remote sensing image fusion method based on a deep convolutional neural network. First, the present invention pre-interpolates the multispectral remote sensing image with low spatial resolution to the same size as the panchromatic image with high spatial resolution. Secondly, the deep convolutional neural network is used to extract the high-frequency spatial structure features of the panchromatic image and the multispectral image. Finally, the extracted high-frequency residual information is added to the original multispectral image to obtain a fused image with high spatial resolution. High-rate multispectral remote sensing images. This method can realize the fusion of low-resolution multispectral images and high-resolution panchromatic images, and obtain remote sensing images with clear structure, hig...

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Abstract

The invention discloses a remote sensing image fusion method based on a deep convolutional neural network, and belongs to the field of remote sensing image processing. Firstly, a multispectral remote sensing image with a low spatial resolution is interpolated in advance to the same size as a panchromatic image with a high spatial resolution; secondly, high-frequency spatial structure characteristics of the panchromatic image and the multispectral image are extracted by using a deep convolutional neural network; and finally, extracted high-frequency residual information and the original multispectral image are added so that a fused multispectral remote sensing image with high spatial resolution is obtained. According to the invention, fusion of a low-resolution multispectral image and a high-resolution panchromatic image can be realized, and a remote sensing image with a clear structure, high spatial resolution and rich spectral information is obtained.

Description

technical field [0001] The invention relates to a remote sensing image fusion method based on a deep convolutional neural network, belonging to the field of remote sensing image processing. Background technique [0002] In recent years, with the development of science and technology and remote sensing technology, remote sensing images have been widely used in various fields, such as urban planning, environmental monitoring, topographic survey, etc. Panchromatic images have high spatial resolution but lack color information, while multispectral images have rich spectral information but low spatial resolution. In order to obtain multispectral images with high spatial resolution, in many cases, we usually fuse multispectral images with low spatial resolution with panchromatic images with rich spatial details to obtain high resolution in both spatial and spectral domains. image, we call it remote sensing image panchromatic sharpening. Remote sensing image panchromatic sharpeni...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50G06N3/04G06N3/08
CPCG06T5/50G06N3/08G06T2207/20221G06T2207/20081G06T2207/20084G06T2207/10036G06T2207/10041G06N3/045
Inventor 黄为伟郑钰辉
Owner NANJING UNIV OF INFORMATION SCI & TECH
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