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Remote Sens. 2014, 6(7), 6365-6385; doi:10.3390/rs6076365

Improved van Zyl Polarimetric Decomposition Lessening the Overestimation of Volume Scattering Power

1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan, Hubei 430079, China
2
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
*
Author to whom correspondence should be addressed.
Received: 30 April 2014 / Revised: 19 June 2014 / Accepted: 27 June 2014 / Published: 8 July 2014
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Abstract

This paper improves van Zyl’s Nonnegative Eigenvalue Decomposition (NNED). Orientation angle compensation and helix scattering are introduced to the decomposition. The volume scattering parameters that explain the most cross-polarized power are selected. If volume scattering and helix scattering explain all cross-polarized power in the measured coherency matrix, then simply perform van Zyl decomposition to the remainder matrix; otherwise, the measured coherency matrix is decomposed into three components, i.e., helix scattering, volume scattering, and one ground scattering. The latter two scattering are all modeled by Neumann’s adaptive depolarizing model, according to which some cross-polarized power is attributed to ground scattering hence the orientation angle randomness of volume scattering and the dominant ground scattering are obtained. In this way, all cross-polarized power could be well explained. Experiments using UAVSAR data showed that more than 99.8% of total pixels are well fitted. Negative power is avoided. Compared with van Zyl decomposition, volume scattering power is reduced by up to 8.73% on average. The given volume scattering power is often lower than that by three latest NNED. View Full-Text
Keywords: polarimetric SAR; polarimetric decomposition; nonnegative eigenvalue decomposition; scattering model polarimetric SAR; polarimetric decomposition; nonnegative eigenvalue decomposition; scattering model
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Cheng, X.; Huang, W.; Gong, J. Improved van Zyl Polarimetric Decomposition Lessening the Overestimation of Volume Scattering Power. Remote Sens. 2014, 6, 6365-6385.

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