Superpixel based graph convolutional neural network for SAR image segmentation

Ilter Türkmenli; Erchan Aptoula; Koray Kayabol

doi:10.1117/12.2599864

12 September 2021 Superpixel based graph convolutional neural network for SAR image segmentation

Ilter Türkmenli, Erchan Aptoula, Koray Kayabol

Proceedings Volume 11862, Image and Signal Processing for Remote Sensing XXVII; 118620K (2021) https://doi.org/10.1117/12.2599864
Event: SPIE Remote Sensing, 2021, Online Only

Abstract

n this study, one of the state-of-the-art computer vision methods, namely superpixel-based graph convolutional networks (GCN), was used to achieve an accurate semantic segmentation of SAR images. In more detail, first, simple linear iterative clustering (SLIC) is used to over-segment the input SAR image into a set of superpixels, then a feature extraction method is employed to extract features from each of the superpixels. U-Net is used as deep feature extractors. Last, GCN architecture is used for node-based classification. We thus intend to exploit the spatial informationvia superpixels, as well the spatial relations among them via node edges. The experiments were conducted on real-world single polarization SAR images obtained from the Sentinel-1 satellite to test the performance of the proposed segmentation method. The results of these experiments show the advantage of the proposed GCN-based method for SAR image segmentation.

Conference Presentation

Citation Download Citation

Ilter Türkmenli, Erchan Aptoula, and Koray Kayabol "Superpixel based graph convolutional neural network for SAR image segmentation", Proc. SPIE 11862, Image and Signal Processing for Remote Sensing XXVII, 118620K (12 September 2021); https://doi.org/10.1117/12.2599864

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