Water Objects Extraction from Polarimetric SAR Imagery Based on Sequential Nonlinear Filtering and Independent Component Analysis
Dong Wang, Ping Qin, Yingying Jennifer Chen · 2009
A new method is proposed for speckle noise suppression and water objects extracting from synthetic aperture radar (SAR) imagery based on sequential nonlinear filtering and independent component analysis. The distribution of SAR image data with multiplicative speckle noise is non-Gaussian and its parameters are unknown. Logarithmic quantification is utilized to transform multiplicative speckle noise to independent additive noise. Speckle noise and image data are separated from multi-polarimetric imagery, and the components with the least speckle index are chosen as the object component automatically by means of ICA while the specific distribution of SAR imagery is unnecessary. Water objects are extracted from the separated object component imagery based on sequential nonlinear filtering according to their lightness and region shape features. The experimental results using ENVISAT ASAR polarimetric imagery show that the proposed method can extract water objects rapidly and accurately.