Remote sensing image super resolution reconstruction method and system based on depth convolution network

A technology of remote sensing image and depth convolution, applied in the field of remote sensing image processing, to achieve fast reconstruction speed, weaken block effect, and strong applicability

Pending Publication Date: 2017-09-01
INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
View PDF0 Cites 30 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In China, Xu Ran and others proposed an SR reconstruction algorithm based on dual-channel convolution, which improved the reconstructi

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 super resolution reconstruction method and system based on depth convolution network
  • Remote sensing image super resolution reconstruction method and system based on depth convolution network
  • Remote sensing image super resolution reconstruction method and system based on depth convolution network

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0020] In the following description, for illustrative purposes, many specific details are set forth in order to provide a comprehensive understanding of one or more embodiments. However, it is obvious that these embodiments can also be implemented without these specific details. In other examples, for the convenience of describing one or more embodiments, well-known structures and devices are shown in the form of block diagrams.

[0021] Hereinafter, various embodiments according to the present invention will be described in detail with reference to the accompanying drawings.

[0022] figure 1 It is a schematic flow diagram of the remote sensing image super-resolution reconstruction method based on the deep convolutional network of the present invention, such as figure 1 As shown, the remote sensing image super-resolution reconstruction method includes:

[0023] Step S1: Convert the remote sensing image to be processed from RGB space to YCbCr space, and separate the brightness space...

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 super resolution reconstruction method and a system based on a depth convolution network. The method comprises steps: a to-be-processed remote sensing image is converted to YCbCr space from RGB space, and brightness space and chromaticity space are separated; a multilayer depth convolution network is built, a super resolution reconstruction model is built based on the multilayer depth convolution network, the super resolution reconstruction model is used for reconstructing the brightness space, and brightness space after reconstruction is obtained; with the brightness space after reconstruction as a guide graph, the chromaticity space is guided for joint bilateral filtering, and chromaticity space after reconstruction is obtained; the brightness space after reconstruction and the chromaticity space after reconstruction are integrated, the to-be-processed remote sensing image after integration is returned to the RGB space from the YCbCr space, a super resolution image is obtained, and the super resolution image has a higher resolution than the to-be-processed remote sensing image. The above method and the system, in a condition of not relying on a multi-temporal remote sensing image sequence in the same scene, realize super resolution reconstruction in view of the remote sensing image, and the image resolution is enhanced.

Description

technical field [0001] The present invention relates to the technical field of remote sensing image processing, and more specifically, to a remote sensing image super-resolution reconstruction method and system based on a deep convolutional network. Background technique [0002] With the in-depth development of remote sensing technology in the fields of ground object observation and target recognition, people's demand for high-resolution remote sensing images is increasing day by day. Improving hardware equipment is the most direct way to obtain high-resolution remote sensing images, but its cost is high, the development period is long, and it will cause problems such as noise and slow transmission rate, and it is not easy to maintain and has poor flexibility. ) reconstruction starts from the image information itself, and reconstructs a high-resolution image from one or more low-resolution images, which is an economical and convenient technology to improve image resolution. ...

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): G06T3/40
CPCG06T3/4007G06T3/4053
Inventor 张洪群李欣韦宏卫吴业炜
Owner INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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