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Freeman/eigenvalue decomposition method of adaptive volume scattering model

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

Active Publication Date: 2017-10-03
XIDIAN UNIV
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  • Description
  • Claims
  • Application Information

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 of adaptive volume scattering model
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  • Freeman/eigenvalue decomposition method of adaptive volume scattering model

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Embodiment 1

[0032] The present invention is a freeman / eigenvalue decomposition method of an adaptive volume scattering model, see figure 1 , including the following steps:

[0033] (1) Input the polarimetric SAR image data matrix:

[0034] 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.

[0035] (2) Exquisite Lee filtering:

[0036] Using the refined Lee filtering method, the polarimetric SAR image is filtered to remove...

Embodiment 2

[0050] The freeman / eigenvalue decomposition method of the adaptive volume scattering model is the same as in embodiment 1, and the new phase difference NPD is obtained by the polarization azimuth angle θ in step (4), including the following steps:

[0051] 4a) Calculate the co-polarization phase difference CPD:

[0052]

[0053] The left side of the above formula represents the exponential form of the complex number, and the co-polarization phase difference CPD is equal to ρ HHVV denotes the co-polarization correlation coefficient. The middle of the above formula represents the general form of the relevant element items of the covariance matrix C of the input polarimetric SAR image, where:

[0054]

[0055]

[0056]

[0057] C 11 ,C 33 ,C 13 is the correlation item of the covariance matrix C.

[0058] 4b) Calculate the cross-polarization phase difference XPD:

[0059]

[0060] The left side of the above formula represents the exponential form of the comp...

Embodiment 3

[0074] The freeman / eigenvalue decomposition method of the self-adaptive volume scattering model is the same as embodiment 1-2, and the threshold value of the new phase difference NPD that is used for judging is determined in the step (6) of the present invention, judges the region where the target is located, and carries out corresponding break down.

[0075] The original hybrid freeman / eigenvalue decomposition algorithm form in the prior art:

[0076]

[0077] α represents the scattering angle, P s Indicates the surface scattered power, P d Indicates the even scattered power, P v Indicates the volume scattered power.

[0078] According to the original mixed freeman / eigenvalue decomposition:

[0079]

[0080]

[0081]

[0082] 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 ...

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Abstract

The invention discloses a freeman / eigenvalue decomposition method and an adaptive volume scattering model, and aims at solving the technical problems that volume scattering components are over-estimated and negative power pixel points are generated in polarization SAR image decomposition. The method comprises the following decomposition processes of: inputting a polarization SAR image data matrix; carrying out delicate Lee filtration and eliminating speckle noise; calculating a polarization azimuth angle to obtain a cross-polarization scattering model, and carrying out azimuth angle compensation; obtaining a new phase difference NPD through the polarization azimuth angle, and judging whether a target is located in an urban region or a natural region according to the NDP; constructing an improved adaptive scattering model; determining a new phase different NDP threshold value and judging a region where the target is located; and synthesizing an RGB image by using three scattering power distributions such as Pd, Pv and Ps and outputting the RGB image. The adaptive volume scattering model can be adapted to different object features, has more correct decomposition result in the artificial regions such as the city and the like, and can be applied to the identification and classification of polarization 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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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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