Freeman/Eigenvalue Decomposition Method for Adaptive Volume Scattering Models

A technology of eigenvalue decomposition and scattering model, applied in the field of image processing, can solve the problem of overestimation of volume scattering, and achieve the effect of reducing the proportion of pixels, increasing the proportion, and suppressing the problem of overestimation of volume scattering

Active Publication Date: 2020-08-04
XIDIAN UNIV
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AI Technical Summary

Problems solved by technology

Compared with the original hybrid freeman / eigenvalue decomposition method, using this method improves the volume scattering overestimation problem and reduces the negative power ratio, but it uses a fixed volume scattering model, and there are still volume scattering overestimation problems and negative power problems

Method used

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  • Freeman/Eigenvalue Decomposition Method for Adaptive Volume Scattering Models
  • Freeman/Eigenvalue Decomposition Method for Adaptive Volume Scattering Models
  • Freeman/Eigenvalue Decomposition Method for Adaptive Volume Scattering Models

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Embodiment 1

[0034] The present invention is a freeman / eigenvalue decomposition method of an adaptive volume scattering model, see figure 1, Including the following steps:

[0035] (1) Input the polarimetric SAR image data matrix:

[0036] Direct input of polarization SAR image coherence matrix T or covariance matrix C, when the input data is coherence matrix T, T contains six matrices T 11 , T 12 , T 13 , T 22 , T 23 , T 33 , represents the polarization information of each pixel in the polarimetric SAR image; when the input data is a covariance matrix C, C contains six matrices C 11 ,C 12 ,C 13 ,C 22,C 23 ,C 33 , represents the polarization information of each pixel in the polarimetric SAR image; the covariance matrix C and the coherence matrix T can be converted to each other. This example uses the polarization coherence matrix T as input.

[0037] (2) Exquisite Lee filtering:

[0038] Using the refined Lee filtering method, the polarimetric synthetic aperture radar SAR im...

Embodiment 2

[0052] The freeman / eigenvalue decomposition method of the adaptive volume scattering model is the same as that of Embodiment 1. In step (4), the new phase difference NPD is obtained by the polarization azimuth angle θ, including the following steps:

[0053] 4a) Calculate the co-polarization phase difference CPD:

[0054]

[0055] The left side of the above equation represents the exponential form of the complex number, and the co-polarization phase difference CPD is equal to ρ HHVV represents the co-polarization correlation coefficient. The middle of the above formula represents the general form of the relevant element terms of the input polarimetric SAR image covariance matrix C, where:

[0056]

[0057]

[0058]

[0059] C 11 ,C 33 ,C 13 is the correlation term of the covariance matrix C.

[0060] 4b) Calculate the cross-polarization phase difference XPD:

[0061]

[0062] The left side of the above equation represents the exponential form of the comp...

Embodiment 3

[0076] The freeman / eigenvalue decomposition method of the adaptive volume scattering model is the same as that of Embodiment 1-2. In step (6) of the present invention, the threshold value of the new phase difference NPD used for judgment is determined, the region where the target is located, and the corresponding break down.

[0077] The original hybrid freeman / eigenvalue decomposition algorithm form in the prior art:

[0078]

[0079] α is the scattering angle, P s is the surface scattering power, P d is the even scattering power, P v represents the volume scattering power.

[0080]According to the original mixed freeman / eigenvalue decomposition:

[0081]

[0082]

[0083] the t above ab , a,b∈(1,2,3) represent the corresponding items of the coherence matrix T of the polarimetric SAR image. The volume scattering power P of each pixel can be obtained from the above formula v , surface scattering power P s , Even-order scattering power P d .

[0084] The gene...

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Abstract

The invention discloses a freeman / eigenvalue decomposition method of an adaptive volume scattering model. The technical problems of overestimation of volume scattering components and generation of negative power pixels in polarimetric SAR image decomposition are solved. The decomposition process is as follows: input the polarimetric SAR image data matrix; refine the Lee filter to eliminate speckle noise; calculate the polarization azimuth θ, obtain the cross-polarization scattering model, and perform azimuth compensation; obtain the new phase difference through the polarization azimuth NPD, judge whether the target is in an urban area or a natural area according to NPD; build an improved adaptive scattering model; determine the new phase difference NPD threshold, and judge the area where the target is located; use P d ,P v ,P s Three kinds of scattered power distributions synthesize RGB image output. The self-adaptive volume scattering model adopted by the invention can adapt to different features of ground objects, especially in urban areas, the decomposition result is more accurate, and can be applied to the identification and classification of polarimetric SAR targets.

Description

technical field [0001] The invention belongs to the technical field of image processing, and is mainly aimed at decomposing polarimetric SAR data, specifically a freeman / eigenvalue decomposition method of an adaptive volume scattering model, which can be applied to the identification and classification of polarimetric SAR targets. Background technique [0002] Polarization synthetic aperture radar (polarization SAR) is a new SAR system based on the traditional SAR system. It measures the full polarization of the object through the combination of different polarization methods, and records the material composition, geometric characteristics, and azimuth of the object. and other information, to achieve a more comprehensive description of the object, and to provide the required specific information for different application scenarios. [0003] Polarimetric target decomposition is the main implementation method of polarimetric SAR image polarization feature extraction. It uses p...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/40G06K9/62
CPCG06V10/30G06F18/24G01S13/9076
Inventor 侯彪焦李成郑伟伟王爽马晶晶马文萍冯婕张小华
Owner XIDIAN UNIV
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