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Dirichlet MRF hybrid model-based polarimetric SAR image classification method

A classification method and hybrid model technology, applied in the field of image processing, can solve the problem of inapplicability of polarimetric SAR data

Active Publication Date: 2016-11-16
XIDIAN UNIV
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However, the disadvantage of this method is that this type of model introduces spatial structure information through the Euclidean distance of the SAR image feature vector, which is not applicable to polarimetric SAR data

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  • Dirichlet MRF hybrid model-based polarimetric SAR image classification method
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[0038] The present invention will be further described below in conjunction with the accompanying drawings.

[0039] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0040] Step 1, input polarimetric SAR image.

[0041] The present invention selects the following two polarization SAR images:

[0042] Polarization SAR image in the Flevoland area: the image size is 320×326 pixels; the equivalent view number is 4; the resolution is 2.5652m×2m; the radar system is AIRSAR;

[0043] Polarization SAR image in the Oberpfaffenhofen area: the image size is 500×450 pixels; the equivalent view number is 2; the resolution is 3m×0.89m; the radar system is ESAR.

[0044] Step 2, extract and normalize the polarized scattering features, and establish a normalized polarized scattering feature space F 1 .

[0045] 2a) Extract N polarimetric scattering features F from the polarimetric SAR image r , r=1,2,...,N, N=17 represents the number of po...

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Abstract

The present invention discloses a Dirichlet MRF hybrid model-based polarimetric SAR image classification method, which aims to solve a problem in the prior art that a quantity of types of the polarimetric SAR images cannot be determined automatically. The method comprises a first step of extracting and normalizing N polarization scattering characteristics of the polarimetric SAR images, and establishing a normalized polarization scattering characteristic space; a second step of reducing noise of the normalized polarization scattering characteristic space point by point, and establishing a polarization scattering characteristic space; a third step of initializing an MRF model by using the polarization scattering characteristic space; a fourth step of estimating prior parameters and likelihood parameters of the polarimetric SAR images according to the initialized MRF model; and a fifth step of estimating a new label field according to the estimated parameters till a largest iteration number of times is reached, and determining the new label field as a classification result of the polarimetric SAR images. Through adoption of the method, the classification accuracy and classification smoothness of a homogeneous region are improved, and edge information is well maintained so as to be used for target detection and identification of the polarimetric SAR images.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a classification method of polarimetric SAR images, which can be used for target detection and recognition of polarimetric SAR images. Background technique [0002] Polarization Synthetic Aperture Radar (SAR) is a high-resolution imaging radar. Its wide use in civilian and military fields requires the support of polarimetric SAR image interpretation technology, and polarimetric SAR image classification is an important technology in the field of machine learning and data mining, as well as one of the important contents of image interpretation. It can provide the overall structure information of the polarimetric SAR image and reveal the essence of the polarimetric SAR image. In recent years, the polarimetric SAR image classification method has been a hot spot in frontier research in this field, among which the random field model is considered to be a powerful ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/22G06F18/2415G06F18/254
Inventor 李明宋婉莹张鹏吴艳
Owner XIDIAN UNIV
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