Polarimetric SAR images classification using deep belief networks with learning features

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 2015-November, Issue , 2015, Pages 2366-2369

  Hou, Biao ^a   Luo, Xiaohuan ^a   Wang, Shuang ^a   Jiao, Licheng ^a   Zhang, Xiangrong ^a  

^a XIDIAN UNIVERSITY   (China)

Author keywords

Deep Belief Networks; Image classification; PolSAR; RBM

Indexed keywords

EID: 84962483072     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2015.7326284     Document Type: Conference Paper

References (8)

1. J. S. Lee and E. Pottier, "Polarimetric, Radar Imaging: From Basics toApplication, " New York: CRC Press, 2009.
2. J. S. Lee, M. R. Grunes, and R. Kwok, "classification of multilook Polarimetric SAR imagery based on complex Wishart distribution, " International, " Journal of Remote Sensing, vol. 15, pp. 2299-2311, 1994.
3. Y. D. Zhang, L. Wu, and G. Wei, "A new classifier for polarimetric SAR images, " Progr. Electromagn. Res., vol. 94, pp. 83-104, 2009
4. L. Zhang, B. Zou, J. Zhang, and Y. Zhang, "Classification of polarimetric SAR image based on support vector machine using multiple-component scattering model and texture features, " EURASIP Journal on Advances in Signal Processing. 2010
5. G. E. Hinton, S. Osindero, and Y. W. Teh, "A fast learning algorithm for deep belief nets, " Neural Comput., vol. 18, no. 7, pp. 1527-1554, 2006.
6. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, "Gradientbased learning applied to document recognition, " Proc. IEEE, vol. 86, pp. 2278-2324, 1998
7. O. Antropov, Y. Rauste, H. Astola, and J. Praks, "Land cover and soil type mapping from spaceborne PolSAR data at L-Band with probabilistic neural network, " IEEE Trans. Geosci. Remote Sens., vol. 52, no. 9, pp. 5256-5270, 2014
8. T. Ince, S. Kiranyaz, and M. Gabbouj, "Evolutionary RBF classifier for polarimetric SAR images, " Expert Syst. Appl., vol. 39, no. 5, pp. 4710-4717, 2012.