10 J J van Zyl Application of cloudes target decomposition theorem to

10 j j van zyl application of cloudes target

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[10] J. J. van Zyl, “Application of cloude’s target decomposition theorem to polarimetric imaging radar data,” in Radar polarimetry , vol. 1748. International Society for Optics and Photonics, 1993, pp. 184–191. [11] R. Touzi, “Target scattering decomposition in terms of roll-invariant target parameters,” IEEE Trans. Geosci. Remote Sens. , vol. 45, no. 1, pp. 73–84, Jan 2007. [12] R. Paladini, L. Ferro Famil, E. Pottier, M. Martorella, F. Berizzi, and E. Dalle Mese, “Lossless and sufficient ψ -invariant decomposition of random reciprocal target,” IEEE Trans. Geosci. Remote Sens. , vol. 50, no. 9, pp. 3487–3501, Sep. 2012. [13] R. Touzi, A. Deschamps, and G. Rother, “Phase of target scattering for wetland characterization using polarimetric c-band sar,” IEEE Trans. Geosci. Remote Sens. , vol. 47, no. 9, pp. 3241–3261, Sep. 2009. [14] R. Touzi, K. Omari, B. Sleep, and X. Jiao, “Scattered and received wave polarization optimization for enhanced peatland classification and fire damage assessment using polarimetric palsar,” IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. , vol. 11, no. 11, pp. 4452–4477, Nov 2018. [15] A. Freeman and S. L. Durden, “A three-component scattering model for polarimetric SAR data,” IEEE Trans. Geosci. Remote Sens. , vol. 36, no. 3, pp. 963–973, May 1998. [16] Y. Yamaguchi, T. Moriyama, M. Ishido, and H. Yamada, “Four- component scattering model for polarimetric SAR image decomposi- tion,” IEEE Trans. Geosci. Remote Sens. , vol. 43, no. 8, pp. 1699–1706, Aug 2005. [17] Y. Yamaguchi, A. Sato, W. Boerner, R. Sato, and H. Yamada, “Four- component scattering power decomposition with rotation of coherency matrix,” IEEE Trans. Geosci. Remote Sens. , vol. 49, no. 6, pp. 2251– 2258, June 2011. [18] W. An, Y. Cui, and J. Yang, “Three-component model-based decom- position for polarimetric sar data,” IEEE Trans. Geosci. Remote Sens. , vol. 48, no. 6, pp. 2732–2739, June 2010. [19] J. J. van Zyl, M. Arii, and Y. Kim, “Model-based decomposition of polarimetric sar covariance matrices constrained for nonnegative eigenvalues,” IEEE Trans. Geosci. Remote Sens. , vol. 49, no. 9, pp. 3452–3459, Sep. 2011. [20] M. Arii, J. J. van Zyl, and Y. Kim, “Adaptive model-based decomposition of polarimetric sar covariance matrices,” IEEE Trans. Geosci. Remote Sens. , vol. 49, no. 3, pp. 1104–1113, March 2011. [21] A. Sato, Y. Yamaguchi, G. Singh, and S. Park, “Four-component scat- tering power decomposition with extended volume scattering model,” IEEE Geosci. Remote Sens. Lett. , vol. 9, no. 2, pp. 166–170, March 2012. [22] G. Singh, Y. Yamaguchi, and S. Park, “General four-component scat- tering power decomposition with unitary transformation of coherency matrix,” IEEE Trans. Geosci. Remote Sens. , vol. 51, no. 5, pp. 3014– 3022, May 2013. [23] J. Lee, T. L. Ainsworth, and Y. Wang, “Generalized polarimetric model- based decompositions using incoherent scattering models,” IEEE Trans. Geosci. Remote Sens. , vol. 52, no. 5, pp. 2474–2491, May 2014. [24] Y. Cui, Y. Yamaguchi, J. Yang, H. Kobayashi, S. Park, and G. Singh, “On complete model-based decomposition of polarimetric sar coherency matrix data,” IEEE Trans. Geosci. Remote Sens. , vol. 52, no. 4, pp. 1991–2001, April 2014. [25] S. Chen, X. Wang, S. Xiao, and M. Sato, “General polarimetric model- based decomposition for coherency matrix,” IEEE Trans. Geosci. Remote Sens. , vol. 52, no. 3, pp. 1843–1855, March 2014. [26] A. Bhattacharya, G. Singh, S. Manickam, and Y. Yamaguchi, “An adaptive general four-component scattering power decomposition with unitary transformation of coherency matrix (AG4U),” IEEE Geosci.

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