Abstract
Abstract. To effectively test the scene heterogeneity for polarimetric synthetic aperture radar (PolSAR) data, in this paper, the distance measure is introduced by utilizing the similarity between the sample and pixels. Moreover, given the influence of the distribution and modeling texture, the K distance measure is deduced according to the Wishart distance measure. Specifically, the average of the pixels in the local window replaces the class center coherency or covariance matrix. The Wishart and K distance measure are calculated between the average matrix and the pixels. Then, the ratio of the standard deviation to the mean is established for the Wishart and K distance measure, and the two features are defined and applied to reflect the complexity of the scene. The proposed heterogeneity measure is proceeded by integrating the two features using the Pauli basis. The experiments conducted on the single–look and multilook PolSAR data demonstrate the effectiveness of the proposed method for the detection of the scene heterogeneity.
Highlights
Polarimetric SAR systems detect and acquire information by radar echoes of various combinations of transmitting and receiving polarizations from scattering media, and the images have been widely accepted as an indispensable method for earth monitoring (Lee and Pottier. 2009)
Two real polarimetric synthetic aperture radar (PolSAR) images are applied to validate the effectiveness of the proposed approach
The distance measure is introduced to describe the spatial heterogeneity for PolSAR data
Summary
Polarimetric SAR systems detect and acquire information by radar echoes of various combinations of transmitting and receiving polarizations from scattering media, and the images have been widely accepted as an indispensable method for earth monitoring (Lee and Pottier. 2009). Polarimetric SAR systems detect and acquire information by radar echoes of various combinations of transmitting and receiving polarizations from scattering media, and the images have been widely accepted as an indispensable method for earth monitoring While the complexity of polarimetric SAR data and the diversity of target scattering complicates the image interpretation and analysis (D’Hondt et al, 2013). The image processing is the emphasis for the application of polarimetric SAR data, such as filtering, decomposition and classification, et al Simultaneously, because of the ability to objectively and quantitatively describe the difference of the scenes, many adaptive filters have been developed by utilizing the heterogeneity to enhance the performances of speckle filtering (Xing et al.,2017, Lang et al.,2015). The scene heterogeneity plays an important role in PolSAR or SAR information extraction and interpretation
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