Title :
Speckle filtering in polarimetric SAR data based on the subspace decomposition
Author :
Gu, Jing ; Yang, Jian ; Zhang, Hao ; Peng, Yingning ; Wang, Chao ; Zhang, Hong
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
Abstract :
In this paper, a new approach to speckle filtering of synthetic aperture radar (SAR) data is presented. We define a parameter space consisting of two orthogonal subspaces-the signal subspace and the noise subspace. Then, the full polarimetric information from the signal subspace is obtained after speckle filtering. In this way, edges of different kinds of targets are preserved. The effectiveness of this method is demonstrated using the National Aeronautics and Space Administration Jet Propulsion Laboratory airborne L-band polarimetric SAR data.
Keywords :
airborne radar; edge detection; geophysical signal processing; geophysical techniques; image denoising; image segmentation; radar imaging; radar polarimetry; remote sensing by radar; speckle; synthetic aperture radar; Jet Propulsion Laboratory; National Aeronautics and Space Administration; airborne L-band polarimetric SAR data; noise subspace; orthogonal subspaces; parameter space; polarimetric information; radar polarimetry; signal subspace; speckle filtering; subspace decomposition; synthetic aperture radar; target edge preservation; Chaos; Covariance matrix; Eigenvalues and eigenfunctions; Information filtering; Information filters; Matrix decomposition; Propulsion; Scattering; Speckle; Synthetic aperture radar; Radar polarimetry; SAR; speckle filtering; synthetic aperture radar;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2004.830610
