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Change detection in synthetic aperture radar images using spatial fuzzy clustering based on the similarity matrix

International Journal on Smart Sensing and Intelligent Systems
Volume 18 (2025): Issue 1 (January 2025)
By:
Open Access
|Jul 2025

Figures & Tables

Figure 1:

Illustration of CNN model architecture. CNN, convolutional neural network.
Illustration of CNN model architecture. CNN, convolutional neural network.

Figure 2:

Illustration of the average pooling operation with a 2 × 2 filter and stride.
Illustration of the average pooling operation with a 2 × 2 filter and stride.

Figure 3:

Flowchart of the proposed method. CNN, convolutional neural network; SFCM, spatial fuzzy clustering membership.
Flowchart of the proposed method. CNN, convolutional neural network; SFCM, spatial fuzzy clustering membership.

Figure 4:

Output of model training.
Output of model training.

Figure 5:

SAR1 image before change.
SAR1 image before change.

Figure 6:

SAR2 image after change.
SAR2 image after change.

Figure 7:

Pre-classification of SAR1 & SAR2 using space matrix calculation and SFCM. SFCM, spatial fuzzy clustering membership.
Pre-classification of SAR1 & SAR2 using space matrix calculation and SFCM. SFCM, spatial fuzzy clustering membership.

Figure 8:

Final change detection output.
Final change detection output.

Comparison with state-of-the-art methods

MethodsAccuracy (%)
Proposed method98.53
FCM [20]91.29
PCAKM [20]90.45
MRFFCM [20]91.27
NR-ELM [21]88.93
DBN [21]87.22
DOI: https://doi.org/10.2478/ijssis-2025-0026 | Journal eISSN: 1178-5608
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Language: English
Submitted on: Mar 7, 2025
Published on: Jul 19, 2025
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year
Keywords:
Deep Learning,
Synthetic Aperture Radar,
Convolutional Neural Networks,
Pattern Recognition,
Noise Robustness,
SAR Imaging Applications
Related subjects:
Engineering,
Introductions and overviews,
Engineering, other

© 2025 Tushar Zanke, Stuti Jagtap, Samrudhi Wath, Snehashish Mulgir, Archana Chaudhari, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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