Speckle reduction for target extraction in synthetic aperture radar images using adaptive space separation based on independent component analysis

2007 ◽  
Author(s):  
Xifeng An ◽  
Yutong Li
Keyword(s):  
Independent Component Analysis ◽  
Synthetic Aperture Radar ◽  
Component Analysis ◽  
Independent Component ◽  
Synthetic Aperture ◽  
Speckle Reduction ◽  
Radar Images ◽  
Target Extraction ◽  
Space Separation ◽  
Aperture Radar

scholarly journals Independent Component Analysis Data Processing Framework for Polarimetric Synthetic Aperture Radar Images

2020 ◽  
Author(s):  
Gabriel Vasile
Keyword(s):  
Independent Component Analysis ◽  
Data Processing ◽  
Synthetic Aperture Radar ◽  
Component Analysis ◽  
Independent Component ◽  
Synthetic Aperture ◽  
Polarimetric Synthetic Aperture Radar ◽  
Radar Images ◽  
Processing Framework ◽  
Aperture Radar

The Independent Component Analysis (ICA) has been recently introduced as a reliable alternative to identify canonical scattering mechanisms within Polarimetric Synthetic Aperture Radar (PolSAR) images. This manuscript addresses two important aspects when applying such methods on real data, namely speckle filtering and statistical classification with ICA. A novel PolSAR data processing framework is introduced by adjusting the Lee's sigma filter to the particular nature of the Touzi's polarimetric decomposition. In its current form, it allows the use of the ICA mixing matrix in the derived speckle filter. An extension of the Fromont at al. iterative segmentation is introduced, equally. This proposed framework is tested using P band airborne PolSAR data acquired for the ESA campaign TropiSAR campaign.

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