Improved mixed Freeman/Eigenvalue decomposition method

Abstract

The invention discloses an improved hybrid Freeman / Eigenvalue decomposition method, and the method comprises the steps: obtaining a complete polarization SAR data coherence matrix, and carrying out the filtering; judging a dominant scattering mechanism at a pixel point in the fully polarimetric SAR data; calculating the surface scattering power, the secondary scattering power and the volume scattering power of the pixel point according to the judgment result of the dominant scattering mechanism; and obtaining a decomposed RGB composite image. According to the invention, the phenomenon of negative power generated by volume scattering power over-estimation, surface scattering and secondary scattering can be effectively solved; different volume scattering models are selected for a natural target area and an artificial target area, and a generalized volume scattering model is introduced for the natural target area, so that the problem that the volume scattering model of the traditional decomposition method is limited and cannot always meet the actual situation is solved. According to the method, a more accurate target scattering characteristic decomposition graph can be obtained, and more accurate classification categories can be obtained in ground object type classification.

Description

technical field [0001] The invention belongs to the technical field of microwave remote sensing, and is mainly aimed at the decomposition of full-polarization SAR data, in particular an improved hybrid Freeman / Eigenvalue decomposition method. Background technique [0002] As an active means of aerospace and aviation remote sensing, microwave imaging technology has the characteristics of all-day and all-weather work, and has a wide range of applications in environmental protection, ocean observation, geological surveying and mapping. Polarimetric Synthetic Aperture Radar (PolSAR) is a development direction of microwave imaging system. It has multiple parameters and multiple channels. matrix, polarization coherence matrix, etc. Polarimetric target decomposition is an important method to extract polarimetric SAR information, and it is also one of the most active directions in the field of polarimetric SAR in recent years. Polarimetric SAR decomposition can be divided into coh...

AI Technical Summary

Problems solved by technology

Some existing target decomposition methods will overestimate the calculation of volume scattering components, but the total energy of the scattering echo matrix is ​​constant, so the surface scattering or secondary scattering power values ​​appear negative; Another part of the target decomposition method uses a volume scattering model that cannot be adaptively adjusted with the full polarization SAR data, and the model cannot always meet the actual situation, resulting in inconsistent results of the decomposition results.

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