RSFNet:  a method for remote sensing image semantic segmentation based on fully convolutional neural networks

Chuanhao Wei; Dezhao Kong; Xuelian Sun; Yu Zhou

doi:10.1117/12.3000799

9 August 2023 RSFNet: a method for remote sensing image semantic segmentation based on fully convolutional neural networks

Chuanhao Wei, Dezhao Kong, Xuelian Sun, Yu Zhou

Author Affiliations +

Proceedings Volume 12782, Third International Conference on Image Processing and Intelligent Control (IPIC 2023); 127821E (2023) https://doi.org/10.1117/12.3000799
Event: Third International Conference on Image Processing and Intelligent Control (IPIC 2023), 2023, Kuala Lumpur, Malaysia

Abstract

The advancement of remote sensing technology has broadened the application scope of remote sensing image data across various fields. Traditional methods, when processing remote sensing images, face limitations in efficiency and generalization capabilities due to their intricate geographical features. In contrast, deep learning segmentation methods exhibit superior performance but struggle with contextual detail loss and multi-scale features. In this paper, we introduce the RSFNet model to tackle these issues. The model employs spatial paths to extract detailed information from low-level features, presents a residual ASPP incorporating an attention mechanism, and utilizes a feature map slicing module to capture small target features. Experimental results show that RSFNet attains 88.38% pixel accuracy (PA) and 81.06% mean intersection over union (mIoU) on the Potsdam dataset, proving its suitability for semantic segmentation of remote sensing images.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chuanhao Wei, Dezhao Kong, Xuelian Sun, and Yu Zhou "RSFNet: a method for remote sensing image semantic segmentation based on fully convolutional neural networks", Proc. SPIE 12782, Third International Conference on Image Processing and Intelligent Control (IPIC 2023), 127821E (9 August 2023); https://doi.org/10.1117/12.3000799

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

Image segmentation

Remote sensing

Convolution

Semantics

Feature extraction

Performance modeling

Small targets

Show All Keywords

Keywords/Phrases

Search In:

Publication Years