Polarimetric SAR image classification using collaborative representation based nearest subspace
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-022-02140-3.pdf
Reference31 articles.
1. Liu, G., Li, Y., Jiao, L., Chen, Y., Shang, R.: Multiobjective evolutionary algorithm assisted stacked autoencoder for PolSAR image classification. Swarm. Evolut. Comput. 60(6), 100794 (2021). https://doi.org/10.1016/j.swevo.2020.100794
2. Fan, C., Hu, Z., Jia, L., et al.: A novel lossless compression encoding framework for SAR remote sensing images. Signal Image Video Process. 15, 441–448 (2021)
3. Yang, R., Hu, Z., Liu, Y., Xu, Z.: A novel polarimetric SAR classification method integrating pixel-based and patch-based classification. IEEE Geosci. Remote Sens. Lett. 17(3), 431–435 (2020)
4. Zhang, Z., Wang, H., Xu, F., Jin, Y.: Complex-valued convolutional neural network and its application in polarimetric SAR image classification. IEEE Trans. Geosci. Remote Sens. 55(12), 7177–7188 (2017)
5. Geng, J., Wang, H., Fan, J., Ma, X.: SAR image classification via deep recurrent encoding neural networks. IEEE Trans. Geosci. Remote Sens. 56(4), 2255–2269 (2018)
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