Abstract
In this paper, the three-component power decomposition for polarimetric SAR (PolSAR) data with an adaptive volume scattering model is proposed. The volume scattering model is assumed to be reflection-symmetric but parameterized. For each image pixel, the decomposition first starts with determining the adaptive parameter based on matrix similarity metric. Then, a respective scattering power component is retrieved with the established procedure. It has been shown that the proposed method leads to complete elimination of negative powers as the result of the adaptive volume scattering model. Experiments with the PolSAR data from both the NASA/JPL (National Aeronautics and Space Administration/Jet Propulsion Laboratory) Airborne SAR (AIRSAR) and the JAXA (Japan Aerospace Exploration Agency) ALOS-PALSAR also demonstrate that the proposed method not only obtains similar/better results in vegetated areas as compared to the existing Freeman-Durden decomposition but helps to improve discrimination of the urban regions.
Highlights
The polarimetric synthetic aperture radar (PolSAR) data have never been so widely available to the remote sensing community as it is today, thanks to the launch of recent systems such as ALOS-PALSAR, RADARSAT-2, TerraSAR-X, etc
The original three-component decomposition proposed by Freeman and Durden [1] models the volume scattering as a cloud of uniformed distributed dipoles, and this leads to the use of a fixed coherency matrix
It is worth noting that the adaptive volume scattering model proposed in this paper is similar to that used by Freeman [11], which can be rewritten in its equivalent coherency matrix form as: (21)
Summary
The polarimetric synthetic aperture radar (PolSAR) data have never been so widely available to the remote sensing community as it is today, thanks to the launch of recent systems such as ALOS-PALSAR, RADARSAT-2, TerraSAR-X, etc. The original three-component decomposition proposed by Freeman and Durden [1] models the volume scattering as a cloud of uniformed distributed dipoles, and this leads to the use of a fixed coherency matrix. A practical issue associated with a fixed volume scattering model is that negative powers which are physically unacceptable may arise for the extracted surface and double-bounce scattering. The surface scattering and double-bounce scattering powers are derived through eigen-decomposition. Such treatment produces a fourth component, called the remainder, which may not necessarily represent any known scattering mechanism. The adaptive parameters are determined by minimizing the power in the covariance matrix after the volume scattering is subtracted
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