Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Remote sensing image unsupervised change detection method based on Siamese network structure

A change detection and remote sensing image technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of unsupervised changes in SAR images, and achieve the improvement of differential feature mining ability, signal-to-noise ratio, and strong feature expression ability. Effect

Active Publication Date: 2020-09-18
SHAANXI UNIV OF SCI & TECH
View PDF2 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to propose a method for unsupervised change detection of remote sensing images based on Siamese network structure, to solve the problem of unsupervised change detection of SAR images, and to highlight change areas and suppress A better balance between speckle noise and higher detection accuracy

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 unsupervised change detection method based on Siamese network structure
  • Remote sensing image unsupervised change detection method based on Siamese network structure
  • Remote sensing image unsupervised change detection method based on Siamese network structure

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] The present invention will be described in further detail below in conjunction with specific examples, but not as a limitation of the present invention.

[0044] like figure 1 As shown, the present invention is based on the unsupervised change detection method of remote sensing images based on the Siamese network structure, and based on the idea of ​​knowledge-driven joint data-driven, prior knowledge is introduced into the deep convolutional neural network, which is described as follows:

[0045] (1) Initialization: The filtering template W in the ALEW algorithm is 3×3. DFF-Siamese takes the pixel-by-pixel neighborhood of the same position in the image before and after the change as input, and the two sets of inputs can be expressed as:

[0046]

[0047]

[0048] in and respectively represent the neighborhood of a certain pixel before and after the change, and the number of input pixel blocks is H×L.

[0049] The input size is set to 5×5. In order to avoid ...

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 discloses a remote sensing image unsupervised change detection method based on a Siamese network structure. The remote sensing image unsupervised change detection method comprises the following steps: (1) initializing parameters; (2) obtaining a difference image; (3) performing pixel-level fusion on the two information complementary difference images in the step (2) by using an adaptive local energy weighting algorithm to obtain a new difference image; (4) adopting a clustering algorithm to realize pre-classification; (5) taking a pre-classification result as a label, and realizing the precise detection of an SAR image change region through a DFF-Siamese network; according to the method, unsupervised change detection of the SAR image is realized, priori knowledge is introduced into the deep convolutional neural network, feature mining is deeper by adding a layer-by-layer difference measurement module in the Siamese network, the learning ability of the network is effectively improved, and a more ideal change detection result can be obtained.

Description

technical field [0001] The invention belongs to the field of image processing and pattern recognition, relates to a remote sensing image change detection method, in particular to a remote sensing image unsupervised change detection method based on a Siamese network structure. Background technique [0002] Remote sensing image change detection is a technology that analyzes the difference of the ground surface through two or more images of the same scene captured at different times. With the rapid development of remote sensing technology, change detection based on remote sensing images has become a key technology for updating geographic big data. Among them, synthetic aperture radar remote sensing images are widely used in environmental monitoring, urban research, disaster assessment, forest resource monitoring, etc. field. Due to the influence of wave interference, there will be errors in the total echo received by the imaging equipment of the radar sensor, resulting in a l...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50G06T5/00G06K9/62G06N3/04G06N3/08
CPCG06T5/50G06N3/08G06T2207/20024G06N3/045G06F18/23G06F18/24G06T5/70
Inventor 雷涛薛丁华张肖张栋
Owner SHAANXI UNIV OF SCI & TECH
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
Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com