Remote sensing image fusion method and system based on dual-branch depth learning network

A deep learning network and remote sensing image fusion technology, applied in the field of remote sensing image processing, can solve the problem that the spatial resolution is not as good as that of full-color images, and achieve good fusion effect.

Inactive Publication Date: 2019-01-04
WUHAN UNIV
View PDF3 Cites 31 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The spectral resolution of multispectral imagery is high, but limited by the physical characteristics of the s

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Remote sensing image fusion method and system based on dual-branch depth learning network
  • Remote sensing image fusion method and system based on dual-branch depth learning network
  • Remote sensing image fusion method and system based on dual-branch depth learning network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0035] The present invention proposes a new remote sensing image fusion network based on deep learning which is currently being actively studied by researchers. Different from the application of deep learning in computer vision, the present invention innovatively uses deep learning to solve the fusion problem of multi-source images in the field of remote sensing. Since multiple data sources are involved, how to coordinate information from different data sources to obtain a better fused image is a difficulty to be solved in the present invention. The network mainly uses convolutional neural networks (CNNs), and a deeper network is designed to extract more effective information for fusion. The fusion network is mainly divi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a remote sensing image fusion method and a remote sensing image fusion system based on a dual-branch depth learning network. The method and the system comprise the following steps that panchromatic images and multi-spectral images as sample data are respectively downsampled by corresponding multiples to obtain training samples; the dual-branch convolution neural network is constructed and trained by using stochastic gradient descent algorithm to obtain the trained dual-branch convolution neural network; the panchromatic image and multispectral image to be fused are inputted into the trained two-branch convolution neural network, and the fused multispectral image with high spatial resolution is obtained. Aiming at the fusion of panchromatic and multi-spectral images in remote sensing images, the invention utilizes the deep-level depth convolution network to more fully extract the characteristics of the images, integrates the complementary information between the two images, and generates multi-spectral images with high spatial resolution.

Description

technical field [0001] The invention belongs to the field of remote sensing image processing and relates to a technical proposal for fusing remote sensing images. Background technique [0002] Remote sensing imagery is an information carrier for satellite sensors to detect and record electromagnetic waves reflected from the surface, and can be used for environmental monitoring, object classification, climate monitoring, etc. Many earth observation satellites (such as Landsat, GeoEye-1, QuickBird, etc.) take a panchromatic image of the same area while shooting multispectral images. Since ground features have different reflection values ​​for electromagnetic waves in different spectral regions, multispectral images can record more information about targets than panchromatic images with a single spectrum. The spectral resolution of the multispectral image is high, but limited by the physical characteristics of the sensor and considering the signal-to-noise ratio, its spatial r...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T5/50G06N3/04
CPCG06T5/50G06T2207/20221G06T2207/10032G06N3/045
Inventor 邵振峰蔡家骏
Owner WUHAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap