Performance of Unsupervised Change Detection Method Based on PSO and K-means Clustering for SAR Images
Abstract
This paper presents unsupervised change detection method to produce more accurate change map from imbalanced SAR images for the same land cover. This method is based on PSO algorithm for image segmentation to layers which classify by Gabor Wavelet filter and then K-means clustering to generate new change map. Tests are confirming the effectiveness and efficiency by comparison obtained results with the results of the other methods. Integration of PSO with Gabor filter and k-means will providing more and more accuracy to detect a least changing in objects and terrain of SAR image, as well as reduce the processing time.References
Feng Gao, Junyu Dong, Bo Li, Qizhi Xu, Cui Xie, “Change detection from synthetic aperture radar images based on neighborhood-based ratio and extreme learning machine,” J. Appl. Remote Sens. 10(4), 046019 (2016), doi: 10.1117/1.JRS.10.046019.
Turgay Celik, " Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and k-Means Clustering", IEEE geoscience and remote sensing letters, vol. 6, no. 4, October 2009.
Xinzheng Zhang, Guo Liu, Ce Zhang, Peter M. Atkinson, Xiaoheng Tan, Xin Jian, Xichuan Zhou and Yongming Li, " Two-Phase Object-Based Deep Learning for Multi-Temporal SAR Image Change Detection", Remote Sensing. 2020.
Karpenko A.P., Seliverstov E.Yu. Review of the particle swarm optimization method (PSO) for a global optimization problem. Nauka i obrazovanie. MGTU im. N.E. Baumana [Science and Education of the Bauman MSTU], 2009, no. 3 (in Russ.). DOI: 10.7463/00309.0116072.
Xinzheng Zhang, Hang Su, Ce Zhang, Peter M. Atkinson, Xiaoheng Tan, Xiaoping Zeng and Xin Jian." A Robust Imbalanced SAR Image Change Detection Approach Based on Deep Difference Image and PCANet", arXiv.org > cs > arXiv:2003.01768, 2020
Feng Gao, Xiao Wang, Junyu Dong, Shengke Wang, " SAR Image Change Detection Based on Frequency Domain Analysis and Random Multi-Graphs", Journal of Applied Remote Sensing,2017
Feng Gao, Junyu Dong, Bo Li, and Qizhi Xu, " Automatic Change Detection in Synthetic Aperture Radar Images Based on PCANet", IEEE geoscience and remote sensing letters, vol. 13, no. 12,2016.
Li Yufeng & He Wei, " Research on SAR image change detection algorithm based on hybrid genetic FCM and image registration", Springer Science+Business Media New York 2017.
Yunhao Gao, Feng Gao, Junyu Dong, and Shengke Wang, " Change Detection from Synthetic Aperture Radar Images Based on Channel Weighting-Based Deep Cascade Network", IEEE journal of selected topics in applied earth observations and remote sensing, 2019.
Wenping Ma, Hui Yang, Yue Wu, Yunta Xiong, Tao Hu, Licheng Jiao and Biao Hou, " Change Detection Based on Multi-Grained Cascade Forest and Multi-Scale Fusion for SAR Images", Remote Sensing. 2019.
Jun Wanga, Xuezhi Yangb, Xiangyu Yanga, Lu Jiaa, Shuai Fanga, "Unsupervised change detection between SAR images based on hypergraphs", ISPRS Journal of Photogrammetry and Remote Sensing 164 (2020) 61–72
J Kennedy, R Eberhart. Particle swarm optimization. // Proceedings of IEEE International conference on Neural Networks. – 1995, pp. 1942 - 1948.
Rupak Chakraborty, Rama Sushil, M. L. Garg, " An Improved PSO-Based Multilevel Image Segmentation Technique Using Minimum Cross-Entropy Thresholding", Arabian Journal for Science and Engineering, King Fahd University of Petroleum & Minerals 2018.
Nameirakpam Dhanachandra, Yambem Jina Chanu, "An image segmentation approach based on fuzzy c-means and dynamic particle swarm optimization algorithm", Springer Science+Business Media, LLC, part of Springer Nature 2020.
Jin Liu, Zilu Wu, Qi Li " A Novel Local Feature Extraction Algorithm Based on Gabor Wavelet Transform", ICAIP 2019: Proceedings of the 2019 3rd International Conference on Advances in Image Processing.
David Bařina, “Gabor Wavelets in Image Processing”, Proceedings of conference and competitions student EEICT 2011, Czech Republic, pp. 1-5.
Deepak Verma, Dr. Vijaypal Dhaka, Shubhlakshmi Agrwa, “An Improved Average Gabor Wavelet Filter Feature Extraction Technique for Facial Expression Recognition”, International Journal of Innovations in Engineering and Technology (IJIET), Vol. 2 Issue 4 August 2013, pp. 35-41.
Youguo Li, Haiyan Wu, " A Clustering Method Based on K-Means Algorithm", 2012 International Conference on Solid State Devices and Materials Science
Joaquín Pérez-Ortega, Nelva Nely Almanza-Ortega, Andrea Vega-Villalobos, Rodolfo Pazos-Rangel, Crispín Zavala-Díaz and Alicia Martínez-Rebollar, " The K-Means Algorithm Evolution", book, April 3rd 2019, DOI: 10.5772/intechopen.85447
T. Celik, “Unsupervised change detection in satellite images using principal component analysis and k-means clustering,” IEEE Geosci. Remote Sens. Lett., vol. 6, no. 4, pp. 772–776, Oct. 2009.
F. Gao, X. Wang, Y. Gao, J. Dong, and S. Wang, “Sea ice change detection in SAR images based on convolutional-wavelet neural networks” IEEE Geosci. Remote Sens. Lett., vol. 16, no. 8, pp. 1240–1244, Aug. 2019.
Maoguo Gong, Meng Jia, Linzhi Su, Shuang Wang & Licheng Jiao, "Detecting changes of the Yellow River Estuary via SAR images based on a local fit-search model and kernel-induced graph cuts" Journal International Journal of Remote Sensing, 2014, Remote sensing of the China seas
Stelios Krinidis ; Vassilios Chatzis, " A Robust Fuzzy Local Information C-Means Clustering Algorithm", IEEE Transactions on Image Processing , May 2010.
Maoguo Gong, Linzhi Su, Meng Jia, Weisheng Chen, " Fuzzy Clustering With a Modified MRF Energy Function for Change Detection in Synthetic Aperture Radar Images", IEEE Transactions on Fuzzy Systems, Feb. 2014.
Downloads
Published
Issue
Section
License
Copyright (c) 2021 International Journal of Electronics and Telecommunications
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
1. License
The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on https://creativecommons.org/licenses/by/4.0/.
2. Author’s Warranties
The author warrants that the article is original, written by stated author/s, has not been published before, contains no unlawful statements, does not infringe the rights of others, is subject to copyright that is vested exclusively in the author and free of any third party rights, and that any necessary written permissions to quote from other sources have been obtained by the author/s. The undersigned also warrants that the manuscript (or its essential substance) has not been published other than as an abstract or doctorate thesis and has not been submitted for consideration elsewhere, for print, electronic or digital publication.
3. User Rights
Under the Creative Commons Attribution license, the author(s) and users are free to share (copy, distribute and transmit the contribution) under the following conditions: 1. they must attribute the contribution in the manner specified by the author or licensor, 2. they may alter, transform, or build upon this work, 3. they may use this contribution for commercial purposes.
4. Rights of Authors
Authors retain the following rights:
- copyright, and other proprietary rights relating to the article, such as patent rights,
- the right to use the substance of the article in own future works, including lectures and books,
- the right to reproduce the article for own purposes, provided the copies are not offered for sale,
- the right to self-archive the article
- the right to supervision over the integrity of the content of the work and its fair use.
5. Co-Authorship
If the article was prepared jointly with other authors, the signatory of this form warrants that he/she has been authorized by all co-authors to sign this agreement on their behalf, and agrees to inform his/her co-authors of the terms of this agreement.
6. Termination
This agreement can be terminated by the author or the Journal Owner upon two months’ notice where the other party has materially breached this agreement and failed to remedy such breach within a month of being given the terminating party’s notice requesting such breach to be remedied. No breach or violation of this agreement will cause this agreement or any license granted in it to terminate automatically or affect the definition of the Journal Owner. The author and the Journal Owner may agree to terminate this agreement at any time. This agreement or any license granted in it cannot be terminated otherwise than in accordance with this section 6. This License shall remain in effect throughout the term of copyright in the Work and may not be revoked without the express written consent of both parties.
7. Royalties
This agreement entitles the author to no royalties or other fees. To such extent as legally permissible, the author waives his or her right to collect royalties relative to the article in respect of any use of the article by the Journal Owner or its sublicensee.
8. Miscellaneous
The Journal Owner will publish the article (or have it published) in the Journal if the article’s editorial process is successfully completed and the Journal Owner or its sublicensee has become obligated to have the article published. Where such obligation depends on the payment of a fee, it shall not be deemed to exist until such time as that fee is paid. The Journal Owner may conform the article to a style of punctuation, spelling, capitalization and usage that it deems appropriate. The Journal Owner will be allowed to sublicense the rights that are licensed to it under this agreement. This agreement will be governed by the laws of Poland.
By signing this License, Author(s) warrant(s) that they have the full power to enter into this agreement. This License shall remain in effect throughout the term of copyright in the Work and may not be revoked without the express written consent of both parties.
