Support vector machine classification of land cover: Application to polarimetric SAR data

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 1, Issue , 2001, Pages 187-189

  Fukuda, S ^a   Hirosawa, H ^a  

^a JAPAN AEROSPACE EXPLORATION AGENCY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; FEATURE EXTRACTION; OPTIMIZATION; PATTERN RECOGNITION SYSTEMS; POLARIMETERS; SYNTHETIC APERTURE RADAR; VECTORS;

KERNEL METHOD; OPTIMAL SEPARATING HYPERPLANE; SUPPORT VECTOR MACHINE CLASSIFICATION;

RADAR IMAGING;

EID: 0035575132     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. EMISAR: An absolutely calibrated polarimetric L- and C-band SAR
2. Optimum texture estimators for SAR clutter
3. Texture and statistical distribution in high resolution polarimetric SAR images
4. Statistical models for polarimetric data: Consequences, testing and validity
5. Single point and spatial statistics of polarimetric SAR imagery