.png){kind=icon}
Return
Classification Method for Fully PolSAR Data Based on Three Novel Parameters
.png){kind=icon}
PRE
AI
DOI：10.1109/LGRS.2013.2245628.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this letter, a new classification method for fully polarimetric synthetic aperture radar (PolSAR) data based on three novel parameters is presented. The three parameters are derived from the eigenspace of the coherency matrix as linear combinations of its three eigenvalues. In the proposed classification method, the maximum value out of the three parameters is determined to assign a label to each image pixel, and the PolSAR image is classified into three classes accordingly. Experimental results based on NASA/JPL AIRSAR L-band data and CSA RADARSAT-2 C-band data illustrate the validity and efficacy of the procedure.
Keywords:
Image classification
radar polarimetry
scattering mechanism
target decomposition
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
16.4
Papers:
1.0W
Citations:
5.1K
Organization
No organization information available
Cited Papers
ShareSaveA Novel Dual Covalent and Non-Covalent Next Generation Inhibitor of Bruton's Tyrosine Kinase LP-168 in Patients with Relapsed/Refractory B Cell Non-Hodgkin Lymphoma: Safety and Efficacy Results from a Phase 1 Study.png)
Blood
OAAI
BloodIF0
OAAIShareSaveShareSave
View more