Remote sensing image change detection method based on hybrid trunk and high and low-frequency attention

Qiuyue Jiang

doi:10.1117/12.3038657

23 August 2024 Remote sensing image change detection method based on hybrid trunk and high and low-frequency attention

Qiuyue Jiang

Proceedings Volume 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024); 132500N (2024) https://doi.org/10.1117/12.3038657
Event: 4th International Conference on Image Processing and Intelligent Control (IPIC 2024), 2024, Kuala Lumpur, Malaysia

Abstract

Remote sensing image change detection technology is rapidly advancing under the impetus of deep learning. In this study, a remote sensing image change detection method based on hybrid backbone and high and low frequency attention modules is proposed for the problems of insufficient extraction of feature components of traditional convolutional neural networks in this field of remote sensing image change detection. The method adopts a hybrid trunk network, and through the attention feature fusion module, the features of the two branches of convolutional neural network and Transformer are fused, which can take care of the extraction of local features and global information. Further, this study integrates high and low frequency attention modules to refine the high frequency details and low frequency background information in the image respectively. The implementation of this method significantly improves the quality and depth of feature extraction. Ultimately, the ability to discriminate and extract the location information and features of interest is strengthened by the coordinate attention module, which improves the recognition accuracy of local details. After extensive experimental testing and validation, it is confirmed that the proposed model achieves a significant improvement in performance compared to existing change detection models.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qiuyue Jiang "Remote sensing image change detection method based on hybrid trunk and high and low-frequency attention", Proc. SPIE 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 132500N (23 August 2024); https://doi.org/10.1117/12.3038657

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Transformers

Feature extraction

Remote sensing

Image processing

Performance modeling

Data modeling

Feature fusion

Keywords/Phrases

Search In:

Publication Years