References
- Baatz, M., and A. Schape. 2000. “Multiresolution Segmentation: An Optimization Approach for High Quality Multiscale Image Segmentation.” In Martin Baatiz and Amo Schape. Proc. AGIS XII, 12–23. Germany: Heidelberg.
- Benedek, C., and T. Szirányi. 2009. “”Change Detection in Optical Aerial Images by a Multi-Layer Conditional Mixed Markov Model.”IEEE Transactions on Geoscience and Remote Sensing 47 (10): 3416–3430. doi:10.1109/TGRS.2009.2022633.
- Bock, M., P. Xofis, J. Mitchley, G. Rossner, and M. Wissen. 2005. “Object oriented Methods for Habitat Mapping at Multiple scales—Case Studies from Northern Germany and Wye Downs, UK.” Journal of Nature Conservation 13 (2): 75–89. doi:10.1016/j.jnc.2004.12.002.
- Bovolo, F., and L. Bruzzone. 2007. “A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain.” IEEE Transactions on Geoscience and Remote Sensing 45 (1): 218–236. doi:10.1109/36.843009.
- Bruzzone, L., and D. F. Prieto. 2000. “Automatic Analysis of the Difference Image for Unsupervised Change Detection.” IEEE Transactions on Geoscience and Remote Sensing 38 (3): 1171–1182. doi:10.1109/36.843009.
- Chatelain, F., J. Y. Tourneret, and J. Inglada. 2008. “Change Detection in Multisensor SAR Images Using Bivariate Gamma Distributions.” IEEE Transactions on Image Process 17 (3): 249–258. doi:10.1109/TIP.2008.916047.
- Dekker, R. J. 1998. “Speckle filtering in Satellite SAR Change Detection Imagery.” International Journal of Remote Sensing 19 (6): 1133–1146. doi:10.1080/014311698215649.
- Du, B., L. Ru, C. Wu, and L. Zhang. 2019. “Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-temporal Remote Sensing Images.” IEEE Transactions on Geoscience and Remote Sensing 57 (12): 9976–9992. doi:10.1109/TGRS.2019.2930682.
- Falco, N., R. R. Marpu, and J. A. Benediktsson. 2016. “A Toolbox for Unsupervised Change Detection Analysis.” International Journal of Remote Sensing 37 (7): 1505–1526. doi:10.1080/01431161.2016.1154226.
- Gao, F., J. Dong, B. Li, and Q. Xu. 2016. “Automatic Change Detection in Synthetic Aperture Radar Images Based on PCANet.” IEEE Geoscience and Remote Sensing Letters 13 (12): 1792–1796. doi:10.1109/LGRS.2016.2611001.
- Gao, F., X. Wang, Y. Gao, J. Dong, and S. Wang. 2019. “Sea Ice Change Detection in SAR Images Based on Convolutional-wavelet Neural Networks.” IEEE Geoscience and Remote Sensing Letters 16 (8): 1–5. doi:10.1109/LGRS.2019.2895656.
- Gong, M., T. Zhan, P. Zhang, and Q. Miao. 2017. “Superpixel-based Difference Representation Learning for Change Detection in Multispectral Remote Sensing Images.” IEEE Transactions on Geoscience and Remote Sensing 55 (5): 2658–2673. doi:10.1109/TGRS.2017.2650198.
- Guo, Q., J. Zhang, and Y. Zhang. 2020. “Multitemporal Image Change Detection Based on AMMF and Spectral Constraint Strategy.” IEEE Transactions on Geoscience and Remote Sensing. doi:10.1109/TGRS.2020.3008016.
- Hou, B., Q. Liu, H. Wang, and Y. Wang. 2020. “From W-net to CDGAN: Bitemporal Change Detection via Deep Learning Techniques.” IEEE Transactions on Geoscience and Remote Sensing 58 (3): 1790–1802. doi:10.1109/TGRS.2019.2948659.
- Im, J., J. R. Jensen, and J. A. Tullis. 2008. “Object-based Change Detection Using Correlation Image Analysis and Image Segmentation.” International Journal of Remote Sensing 29 (2): 399–423. doi:10.1080/01431160601075582.
- Levinshtein, A., A. Stere, K. N. Kutulakos, D. J. Fleet, K. Siddiqi, and K. Siddiqi. 2009. “TurboPixels: Fast Superpixels Using Geometric Flows.” IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (12): 2290–2297. doi:10.1109/TPAMI.2009.96.
- Li, L., X. Li, Y. Zhang, L. Wang, and G. Ying. 2016. “Change Detection for High-resolution Remote Sensing Imagery Using Object-oriented Change Vector Analysis Method,” in Proc. IEEE International Geoscience and Remote Sensing Symposium. (IGARSS), Beijing, China, 2873–2876.
- Nielsen, A. A. 2007. “The Regularized Iteratively Reweighted Mad Method for Change Detection in Multi-and Hyperspectral Data.” IEEE Transactions on Image Process 16 (2): 463–478. doi:10.1109/TIP.2006.888195.
- Pham, M., G. Mercier, and J. Michel. 2016. “Change Detection between SAR Image Using a Pointwise Approach and Graph Theory.” IEEE Transactions on Geoscience and Remote Sensing 54 (4): 1171–1182. doi:10.1109/TGRS.2015.2493730.
- Saha, S., F. Bovolo, and L. Bruzzone. 2019. “Unsupervised Deep Change Vector Analysis for Multiple-change Detection in VHR Images.” IEEE Transactions on Geoscience and Remote Sensing 57 (6): 3677–3693. doi:10.1109/TGRS.2018.2886643.
- Shi, W., M. Zhang, H. Ke, X. Fang, Z. Zhan, and S. Chen. 2020. “Landslide Recognition by Deep Convolutional Neural Network and Change Detection.” IEEE Transactions on Geoscience and Remote Sensing. doi:10.1109/TGRS.2020.3015826.
- Singh, A. 2010. “Review Article Digital Change Detection Techniques Using Remotely-sensed Data.” International Journal of Remote Sensing 10 (6): 989–1003. doi:10.1080/01431168908903939.
- Wan, L., Y. Xiang, and H. You. 2020. “An Object-based Hierarchical Compound Classification Method for Change Detection in Heterogeneous Optical and SAR Images.” IEEE Transactions on Geoscience and Remote Sensing. doi:10.1109/TGRS.2019.2930322.
- Wan, L., T. Zhang, and H. You. 2018. “Object-based Multiscale Method for SAR Image Change Detection.” Journal of Applied Remote Sensing 12 (2): 025004. doi:10.1117/1.JRS.12.025004.
- Wang, J., X. Yang, L. Jia, X. Yang, and Z. Dong. 2019. “Pointwise SAR Image Change Detection Using Stereo-graph Cuts with Spatio-temporal Information.” Remote Sensing Letters 10 (5): 421–429. doi:10.1080/2150704X.2018.1562581.
- Wang, J., X. Yang, L. Jia, F. Zhou, and J. Ai. 2017. “Pointwise Approach for Change Detection between Synthetic Aperture Radar Images Using Bilaterally Weighted Graph and Irregular Markov Random Field.” Journal of Applied Remote Sensing 11 (2): 026031. doi:10.1117/1.JRS.11.026031.
- Wu, J., B. Li, W. Ni, W. Yan, and H. Zhang. 2020. “Optimal Segmentation Scale Selection for Object-based Change Detection in Remote Sensing Image Using Kullback-Leibler Divergence.” IEEE Geoscience and Remote Sensing Letters 17 (7): 1124–1128. doi:10.1109/LGRS.2019.2943406.
- Wu, T., J. Luo, J. Fang, J. Ma, and X. Song. 2018. “Unsupervised Object-based Change Detection via a Weibull Mixture Model-based Binarization for High-resolution Remote Sensing Images.” IEEE Geoscience and Remote Sensing Letters 15 (1): 63–67. doi:10.1109/LGRS.2017.2773118.
- Yousif, O., and Y. Ban. 2017. “A Novel Approach for Object-based Change Image Generation Using Multitemporal High-resolution SAR Images.” International Journal of Remote Sensing 38 (7): 1765–1787. doi:10.1080/01431161.2016.1217442.
- Zhang, Y., D. Peng, and X. Huang. 2018. “Object-based Change Detection for VHR Images Based on Multiscale Uncertainty Analysis.” IEEE Geoscience and Remote Sensing Letters 15 (1): 989–1003. doi:10.1109/LGRS.2017.2763182.
- Zhuang, H., K. Deng, Y. Yang, and H. Fan. 2017. “An Approach Based on Discrete Wavelet Transform to Unsupervised Change Detection in Multispectral Images.” International Journal of Remote Sensing 38 (17): 4914–4930. doi:10.1080/01431161.2017.1331475.