Speckle suppression method for polarized SAR (Synthetic Aperture Radar) data based on non-local mean value fused with PCA (Polar Cap Absorption)

Abstract

The invention discloses a speckle noise suppression method for polarized SAR (Synthetic Aperture Radar) data based on a non-local mean value fused with PCA (Polar Cap Absorption), which mainly solves the problems that speckle noises in a homogeneous region can not be well filtered and the edge detailed information can not be effectively maintained in the traditional polarized SAR filtering method. The implementation process of the method comprises the following steps of: (1) inputting a coherence matrix T of the polarized SAR data; (2) maintaining a bright target for the coherence matrix T; (3) solving a characteristic vector of span data by utilizing a PCA method; (4) filtering the non-local mean value for elements of the coherence matrix T, wherein a filtering weight value is obtained by calculating the characteristic vector of the span data; and (5) generating a pcolor by utilizing the filtered coherence matrix T through a Pauli vector method. Compared with the prior art, the speckle noise suppression method remarkably improves the capability of speckle noise suppression of the polarized SAR data, can effectively smoothen the homogeneous region and maintain the edge detailed information, and can be used for the pretreatment process of the polarized SAR data.

Description

technical field [0001] The invention belongs to the technical field of image data processing, in particular to a method for suppressing coherent spots, which can be used for denoising polarimetric SAR data. Background technique [0002] With the development of radar technology, polarization SAR has become the development trend of SAR. Polarization SAR can obtain more abundant target information, which is conducive to improving target detection, identification and classification capabilities, etc., which reflects the advantages of polarization SAR system. , but it suffers from coherent speckle noise, just like SAR. Therefore, the suppression of coherence speckle has become an enduring research topic. For polarimetric SAR data, the purpose of speckle suppression is to suppress coherent speckle while maintaining the polarization characteristics, edge details and texture information of the data. There are many existing methods for speckle suppression of polarimetric SAR data, ...

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Problems solved by technology

[0003] 1) Polarization whitening filter PWF is the earliest filtering method. This method completes the coherent speckle suppression of span data by optimizing the combination of polarization SAR data scattering matrix elements, but the disadvantage of this method is that it only affects the polarization SAR The span data in the data is subject to coherent speckle suppression, while the elements of the other polarimetric SAR data are not subject to coherent speckle suppression

[0004] 2) The most classic method is refined polarized Lee filtering, which uses edge windows for filtering. The filtered data has a significant effect in maintaining the characteristics of the edge. However, the filtering effect is not particularly ideal in maintaining texture detail information. Therefore, in the suppression of coherent speckles, some original characteristics of the data cannot be well preserved

[0005] 3) The newly proposed improved sigma filter solves the shortcomings of the original sigma filter that the dark pixels are not filtered and there are errors in the filtered data, and effectively maintains the bright target pixel. The smoothness of the texture area is better than the refined polarization Lee filtering method, but in the processing of edges and textures, due to the influence of coherent speckle noise, this kind of filtering still cannot best distinguish coherent speckle noise and edge texture information, making it useful The edge texture information cannot be completely preserved

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