Improved four-component based polarimetric synthetic aperture radar image decomposition

Scattering mechanism ambiguity, negative power problem, and complete utilisation of coherency matrix elements have been the major challenges of the model-based decomposition methods. In this study, the aforementioned issues are addressed simultaneously with an improved four-component decomposition method. In the proposed method, helix scattering power is obtained conventionally, while helix angle compensation is used parallelly for the pixels where helix scattering power is overestimated. In the next step, volume scattering power is determined through the eigen-decomposition approach. Both steps are performed by ensuring the positive semidefinite attribute of the coherency matrix after subtracting helix and volume scattering contributions. The next two scattering powers of surface and dihedral components are derived through the decomposition of the remainder rank-2 coherency matrix into two rank-1 matrices. The experimental validation of the proposed method is carried out on the urban environment of two Indian cities where one can easily find out the random streets distribution and unplanned population settlement. The experimental analyses on these dense and complex urban areas indicate that with the proposed decomposition methodology, non-negative scattering powers are obtained and scattering mechanism ambiguity is greatly suppressed.