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Performance Evaluation of Change Detection in SAR Images Based on Hybrid Antlion DWT Fuzzy c-Means Clustering Cover

Performance Evaluation of Change Detection in SAR Images Based on Hybrid Antlion DWT Fuzzy c-Means Clustering

Cybernetics and Information Technologies
Volume 21 (2021): Issue 2 (June 2021)
By:
Open Access
|Jul 2021

References

  1. 1. Gong, M., Z. Zhou, J. Ma. Change Detection in Synthetic Aperture Radar Images Basedon Image Fusion and Fuzzy Clustering. – IEEE Transactions on Image Processing, Vol. 21, 2012, No 4, pp. 2141-2151.<a href="https://doi.org/10.1109/TIP.2011.217070221984509" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/TIP.2011.217070221984509</a>
    Search in Google ScholarBack to article
  2. 2. Jakka, T. K., Y. Mallikarjuna Reddy, B. Prabhakara Rao. GWDWT-FCM: Change Detection in SAR Images Using Adaptive Discrete Wavelet Transform with Fuzzy c-Mean Clustering. – Journal of the Indian Society of Remote Sensing, Vol. 47, 2019, No 3, pp. 379-390.<a href="https://doi.org/10.1007/s12524-018-0901-0" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1007/s12524-018-0901-0</a>
    Search in Google ScholarBack to article
  3. 3. Kumar, J. T., Y. M. Reddy, B. P. Rao. Image Fusion of Remote Sensing Images Using ADWT with ABC Optimization Algorithm. – International Journal of Innovative Technology and Exploring Engineering (IJITEE), Vol. 8, 2019, Issue 11. ISSN: 2278-3075.<a href="https://doi.org/10.35940/ijitee.K2309.0981119" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.35940/ijitee.K2309.0981119</a>
    Search in Google ScholarBack to article
  4. 4. Kumar, J. T., Y. M. Reddy, B. P. Rao. Change Detection in Sarimages Based on Artificial Bee Colony Optimization with Fuzzy c-Means Clustering. – International Journal of Recent Technology and Engineering (IJRTE), Vol. 7, 2018, Issue 4. ISSN: 2277-3878.
    Search in Google ScholarBack to article
  5. 5. Kumar, J. T., Y. Mallikarjuna Reddy, B. Prabhakara Rao. WHDA-FCM: Wolf Hunting-Based Dragonfly with Fuzzy c-Mean Clustering for Change Detection in SAR Images. – The Computer Journal, Section B: Computer and Communications Networks and Systems, Vol. 63, February 2020, Issue 2, pp. 308-321.<a href="https://doi.org/10.1093/comjnl/bxz130" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1093/comjnl/bxz130</a>
    Search in Google ScholarBack to article
  6. 6. Inglada, J., G. Mercier. A New Statistical Similarity Measure for Change Detection in Multitemporal SAR Images and Its Extension to Multiscale Change Analysis. – IEEE Trans. Geosci. Remote Sens., Vol. 45, 2017, No 5, pp. 1432-144510.1109/TGRS.2007.893568
    Search in Google ScholarBack to article
  7. 7. Singh, A. Digital Change Detection Techniques Using Remotely Sensed Data. – International Remote Sensing, Vol. 10, 1989, No 6, pp. 989-1003.<a href="https://doi.org/10.1080/01431168908903939" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1080/01431168908903939</a>
    Search in Google ScholarBack to article
  8. 8. Rignot, E. J. M., J. J. Van Zyl. Change Detection Techniques for ERS-1 SAR Data. – IEEE Trans. Geosci. Remote Sens., Vol. 31, 1993, No 4, pp. 896-906.<a href="https://doi.org/10.1109/36.239913" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/36.239913</a>
    Search in Google ScholarBack to article
  9. 9. Mirjalili1, S. Dragonfly Algorithm: A New Meta-Heuristic Optimization Technique for Solving Single-Objective, Discrete, and Multi-Objective Problems. – Neural Comput&Applic, Vol. 27, 2016, pp. 1053-1073.<a href="https://doi.org/10.1007/s00521-015-1920-1" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1007/s00521-015-1920-1</a>
    Search in Google ScholarBack to article
  10. 10. SreeRanjini, K. S., S. Murugan. Memory-Based Hybrid Dragonfly Algorithm for Numerical Optimization Problems. – Expert Systems with Applications, Vol. 83, 2017, pp. 63-78.<a href="https://doi.org/10.1016/j.eswa.2017.04.033" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1016/j.eswa.2017.04.033</a>
    Search in Google ScholarBack to article
  11. 11. Çigdeminan, A., H. Gulkan. A Modified Dragonfly Optimization Algorithm for Single- and Multiobjective Problems Using Brownian Motion. – Hindawi Computational Intelligence and Neuroscience, 2019. Article ID 6871298. 17 p.<a href="https://doi.org/10.1155/2019/6871298658931031281336" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1155/2019/6871298658931031281336</a>
    Search in Google ScholarBack to article
  12. 12. Vrionis, T. D., X. I. Koutiva, N. A. Vovos. A Genetic Algorithm-Based Low Voltage Ride-Through Control Strategy for Grid Connected Doubly Fed Induction Wind Generators. – IEEE Transactions on Power Systems, Vol. 29, 2014, No 3, pp. 1325-1334.<a href="https://doi.org/10.1109/TPWRS.2013.2290622" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/TPWRS.2013.2290622</a>
    Search in Google ScholarBack to article
  13. 13. Hui, Z., Y. Fei. A Novel Fuzzy Clustering Recommendation Algorithm Based on PSO. – Cybernetics and Information Technologies, Vol. 14, 2014, No 1, pp. 108-117.<a href="https://doi.org/10.2478/cait-2014-0048" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.2478/cait-2014-0048</a>
    Search in Google ScholarBack to article
  14. 14. Zhang, J., P. Xia. An Optimized Scheduling Algorithm on a Cloud Workflow Using a Discrete Particle Swarm. –Cybernetics and Information Technologies, Vol. 14, 2014, No 1, pp. 25-39.<a href="https://doi.org/10.2478/cait-2014-0003" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.2478/cait-2014-0003</a>
    Search in Google ScholarBack to article
  15. 15. Yan, W., S. Shi, L. Pan, G. Zhang. Unsupervised Change Detection in SAR Images Based on Frequency Difference and a Modified Fuzzy c-Means Clustering. – International Journal of Remote Sensing, Vol. 39, 2018, No 10, pp. 3055-3075.<a href="https://doi.org/10.1080/01431161.2018.1434325" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1080/01431161.2018.1434325</a>
    Search in Google ScholarBack to article
  16. 16. Qiu, F., J. Berglund, J. R. Jensen, P. Thakkar, D. Ren. Speckle Noise Reduction in SAR Imagery Using a Local Adaptive Median Filter. –GIScience and Remote Sensing, Vol. 3, 2004, pp. 244-266.<a href="https://doi.org/10.2747/1548-1603.41.3.244" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.2747/1548-1603.41.3.244</a>
    Search in Google ScholarBack to article
  17. 17. Zhuang, H., Z. Tan, K. Deng, H. Fan. It is a Misunderstanding that Log-Ratio Outperforms Ratio in Change Detection of SAR Images. – European Journal of Remote Sensing, Vol. 52, 2019, No 1, pp. 484-492.<a href="https://doi.org/10.1080/22797254.2019.1653226" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1080/22797254.2019.1653226</a>
    Search in Google ScholarBack to article
  18. 18. Vijaya Geetha, R., S. Kalaivani. Laplacian Pyramid-Based Change Detection in Multitemporal SAR Images. – European Journal of Remote Sensing, Vol. 5, 2019.<a href="https://doi.org/10.1080/22797254.2019.1640077" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1080/22797254.2019.1640077</a>
    Search in Google ScholarBack to article
  19. 19. Liu, T., C. Q. Guo, Y. Yuan, W. Li, Q. Yan. An Improved Ant Lion Optimization Algorithm and Its Application in Hydraulic Turbine Governing System Parameter Identification. – Energies, Vol. 11, 2018, pp. 1-15.<a href="https://doi.org/10.3390/en11010095" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.3390/en11010095</a>
    Search in Google ScholarBack to article
  20. 20. Vrionis, T., X. Koutiva, Nicholas. A Genetic Algorithm-Based Low Voltage Ride-Through Control Strategy for Grid Connected Doubly Fed Induction Wind Generators. – IEEE Transactions on Power Systems, 2014, Vol. 29, No 3, pp. 1325-1334.<a href="https://doi.org/10.1109/TPWRS.2013.2290622" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/TPWRS.2013.2290622</a>
    Search in Google ScholarBack to article
  21. 21. Mirjalili, S. The Ant Lion Optimizer. – Adv. Eng. Software, Vol. 83, 2015, pp. 80-98.<a href="https://doi.org/10.1016/j.advengsoft.2015.01.010" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1016/j.advengsoft.2015.01.010</a>
    Search in Google ScholarBack to article
  22. 22. Zhao, M., Q. Ling, F. Li. An Iterative Feedback-Based Change Detection Algorithm for Flood Mapping in SAR Images. – IEEE Geoscience and Remote Sensing Letters, Vol. 16, February 2019, No 2, pp. 231-235.<a href="https://doi.org/10.1109/LGRS.2018.2871849" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/LGRS.2018.2871849</a>
    Search in Google ScholarBack to article
  23. 23. Li, H., Q. Zhao, G. Yang, K. Fu, W. J. Emery. Robust Semi-NMF with Total Variation for Unsupervised SAR Image Change Detection. – Electronics Letters, Vol. 54, 12.07.2018, No 14, pp. 892-894.
    Search in Google ScholarBack to article
  24. 24. Lazarov, A., C. Minchev. ISAR Image Recognition Algorithm and Neural Network Implementation. – Cybernetics and Information Technologies, Vol. 17, 2017, No 4, pp. 183-199.<a href="https://doi.org/10.1515/cait-2017-0048" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1515/cait-2017-0048</a>
    Search in Google ScholarBack to article
  25. 25. Hou, B., Q. Wei, Y. Zheng, S. Wang. Unsupervised Change Detection in SAR Image Based on Gauss-Log Ratio Image Fusion and Compressed Projection. – IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 7, August 2014, No 8, pp. 3297-3317.<a href="https://doi.org/10.1109/JSTARS.2014.2328344" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/JSTARS.2014.2328344</a>
    Search in Google ScholarBack to article
  26. 26. Zheng, Y., X. Zhang, B. Hou, G. Liu. Using Combined Difference Image and $k$-Means Clustering for SAR Image Change Detection. – IEEE Geoscience and Remote Sensing Letters, Vol. 11, March 2014, No 3, pp. 691-695.<a href="https://doi.org/10.1109/LGRS.2013.2275738" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/LGRS.2013.2275738</a>
    Search in Google ScholarBack to article
  27. 27. Zhang, X., J. Chen, H. Meng. A Novel SAR Image Change Detection Based on Graph-Cut and Generalized Gaussian Model. – IEEE Geoscience and Remote Sensing Letters, Vol. 10, January 2013, No 1, pp. 14-18.<a href="https://doi.org/10.1109/LGRS.2012.2189867" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/LGRS.2012.2189867</a>
    Search in Google ScholarBack to article
  28. 28. Gong, M., Z. Zhou, J. Ma. Change Detection in Synthetic Aperture Radar Images Based on Image Fusion and Fuzzy Clustering. – IEEE Transactions on Image Processing, Vol. 21, April 2012, No 4, pp. 2141-2151.<a href="https://doi.org/10.1109/TIP.2011.217070221984509" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/TIP.2011.217070221984509</a>
    Search in Google ScholarBack to article
  29. 29. Moser, G., S. B. Serpico. Unsupervised Change Detection From Multichannel SAR Data by Markovian Data Fusion. – IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, July 2009, No 7, pp. 2114-2128.<a href="https://doi.org/10.1109/TGRS.2009.2012407" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/TGRS.2009.2012407</a>
    Search in Google ScholarBack to article
DOI: https://doi.org/10.2478/cait-2021-0018 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Journal RSS Feed
Language: English
Page range: 45 - 57
Submitted on: Jul 20, 2020
Accepted on: Feb 23, 2021
Published on: Jul 1, 2021
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year
Keywords:
ADWT,
ALO Algorithm,
HALO Algorithm,
GA Algorithm,
PSO Algorithm
Related subjects:
Computer sciences,
Information technology

© 2021 J. Thrisul Kumar, B. M. S. Rani, M. Satish Kumar, M. V. Raju, K. Maria Das, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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