assessment of capability of the target decomposition features in sea oil pollution detection using polarimetric sar data

in this paper, the potential of polarimetric sar data using target decomposition features to detect oil pollutions are evaluated. for this purpose, the values of power, phase and magnitude of all of the polarization channels (hh, vv, hv and vh) and decomposition features i.e. freeman, yamaguchi, vanzyl and krogager are computed. then, to detect oil pollutions, different combinations of these features by support vector machine classifier, are classified. thus, in addition to evaluating the ability of each of the used target decomposition methods, the most appropriate method for oil pollution detection are identified. the proposed method are conducted on full polarimetric sar data acquired from palsar sensor of alos satellite. evaluation results indicated that vv polarization than hh polarization and the power value relative to magnitude to oil pollution detection are more suitable. among the target decomposition methods, krogager target decomposition method with overall accuracy of 97.3% provides the best result.