Share Email Print
cover

Proceedings Paper

The effect of desying angle on polarimetric SAR image decomposition
Author(s): Boussad Azmedroub; Mounira Ouarzeddine; Boularbah Souissi
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Polarimetric image decomposition is nowadays among the most important applications of multi-polarization, multifrequency SAR radar images. With the growth of new satellite missions equipped with fully polarimetric modes there is a strong need for accurate methods and for new approaches to handle the huge data coming from different airborne and space borne missions and to understand better the several and different mechanisms that occur in a resolution cell. We are interested in this paper in polarimetric SAR image decomposition that makes a comparison between Yamaguchi decomposition called also the four component decomposition before and after image compensation from the orientation angle. This latter affects directly the scattering mechanisms and induces errors in the decomposition results especially in urban area where there are complex structures. We demonstrate with power profiles and with RGB color composite images that the volume scattering type decreases drastically after deorientation, whereas the helix scattering type is not sensitive to orientation. The test site is situated in the north of Algiers city and the satellite data is a fully polarimetric acquisition in C band. Results are in a high agreement with Google earth optical image.

Paper Details

Date Published: 14 February 2015
PDF: 5 pages
Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94450R (14 February 2015); doi: 10.1117/12.2180747
Show Author Affiliations
Boussad Azmedroub, Univ. of Science and Technology Houari Boumediene (Algeria)
Mounira Ouarzeddine, Univ. of Science and Technology Houari Boumediene (Algeria)
Boularbah Souissi, Univ. of Science and Technology Houari Boumediene (Algeria)


Published in SPIE Proceedings Vol. 9445:
Seventh International Conference on Machine Vision (ICMV 2014)
Antanas Verikas; Branislav Vuksanovic; Petia Radeva; Jianhong Zhou, Editor(s)

© SPIE. Terms of Use
Back to Top