Name
Abstract | ||
|---|---|---|
There exist 9 independent polarization parameters in the coherency or covariance matrix as the second order statistics. Various decomposition methods have been presented based on the physical scattering model using these parameters. However, none of them accounts for all polarimetric information, typically leaving T13 element un-accounted in the coherency matrix. This paper presents a complete four-component scattering power decomposition method using all polarimetric information. Using double unitary transformation of measured coherency matrix, it is possible to eliminate T23 element, which results in a reduction of polarization parameters from 9 to 7. Then by unitary transformation of expansion matrices, it becomes possible to account for T13 term, which has never been accounted for in the physical model-based decomposition. By the double unitary transformations to minimize the T33 component, all polarimetric parameters are accounted. This methodology also reduces the negative power problem significantly. This method is a further extension of the existing four-component decomposition. The four scattering powers (surface, double bounce, volume, helix) are assigned to blue, red, green, and yellow to compose full-color image. An example image of San Francisco area acquired with ALOS-PALSAR is shown to validate the decomposed result. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IGARSS.2012.6351629 | IGARSS |
Keywords | Field | DocType |
san francisco,synthetic aperture radar,scattering power decomposition,statistics,four-component scattering power decomposition method,polarimetry,covariance matrices,physical scattering model,independent polarization parameters,second order statistics,expansion matrices,geophysical image processing,double unitary transformation,full polarimetric information,alos-palsar,coherency matrix measurement,radar imaging,full-color image,radar polarimetry,covariance matrix,mathematical model,matrix decomposition,scattering,remote sensing | Polarimetry,Computer science,Matrix (mathematics),Remote sensing,Unitary transformation,Polarization (waves),Decomposition method (constraint satisfaction),Unitary state,Scattering,Covariance matrix | Conference |
ISSN | ISBN | Citations |
2153-6996 E-ISBN : 978-1-4673-1158-8 | 978-1-4673-1158-8 | 4 |
PageRank | References | Authors |
0.87 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yoshio Yamaguchi | 1 | 246 | 49.57 |
| Gulab Singh | 2 | 135 | 20.16 |
| Sang-Eun Park | 3 | 201 | 24.33 |
| Hiroyoshi Yamada | 4 | 161 | 36.65 |