Method of unsupervised segmentation of polarimetric synthetic-aperture-radar (SAR) image data into classes involves selection of classes on basis of multidimensional fuzzy clustering of logarithms of parameters of polarimetric covariance matrix. Data in each class represent parts of image wherein polarimetric SAR backscattering characteristics of terrain regarded as homogeneous. Desirable to have each class represent type of terrain, sea ice, or ocean surface distinguishable from other types via backscattering characteristics. Unsupervised classification does not require training areas, is nearly automated computerized process, and provides nonsubjective selection of image classes naturally well separated by radar.
Unsupervised Segmentation Of Polarimetric SAR Data
NASA Tech Briefs ; 18 , 7
1994-07-01
Miscellaneous
No indication
English
Unsupervised Segmentation of Polarimetric SAR Data
Online Contents | 1994
Segmentation Of Polarimetric SAR Data
NTRS | 1994
|Segmentation of Polarimetric SAR Data
Online Contents | 1994
Unsupervised Classification Preserving Polarimetric Scattering Characteristics
British Library Conference Proceedings | 2013
|Histogram-Based Segmentation of ALOS Polarimetric SAR Data
British Library Conference Proceedings | 2009
|