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HAN Jiqu, MENG Junmin, ZHAO Junsheng. Feature extraction and its criticality analysis for oil spill detection in synthetic aperture radar images[J]. Haiyang Xuebao, 2013, 35(1): 85-93. doi: 10.3969/j.issn.0253-4193.2013.01.010
Citation: HAN Jiqu, MENG Junmin, ZHAO Junsheng. Feature extraction and its criticality analysis for oil spill detection in synthetic aperture radar images[J]. Haiyang Xuebao, 2013, 35(1): 85-93. doi: 10.3969/j.issn.0253-4193.2013.01.010

Feature extraction and its criticality analysis for oil spill detection in synthetic aperture radar images

doi: 10.3969/j.issn.0253-4193.2013.01.010
  • Received Date: 2011-10-04
  • Rev Recd Date: 2012-06-03
  • In terms of the methodology of oil spill identifying in SAR images, it is usually arbitrary to select qualitative or/and quantitative features for classifying dark objects as oil spill or look-alikes. The features selected in different classification models are not the same. The feature extraction and the criticality analysis are made in SAR images. Its aim is to apply the minimum distance method to discriminating oil spills from look-alikes. First, through correlation analysis, the redundancy is removed. Next,a criticality coefficient is introduced to quantitatively study the criticality of features. Then, distinguishing features are extracted. Sequentially, the dimension of feature vector is reduced to fit for the application research of the minimum distance method.
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