Scattering energy and stack self-code-based polarimetric SAR image classification method

A classification method and self-encoding technology, applied in the field of image processing, can solve problems affecting the classification accuracy of polarization synthetic aperture radar SAR images and unreasonable feature extraction, so as to improve classification efficiency, overcome the decline of classification accuracy, and improve classification accuracy Effect

Active Publication Date: 2018-01-09
XIDIAN UNIV
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Problems solved by technology

Although this method combines the texture characteristics of the power image, it still has the disadvantage that when using the deep neural network to extract the features of the polarimetric synthetic ap...

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  • Scattering energy and stack self-code-based polarimetric SAR image classification method
  • Scattering energy and stack self-code-based polarimetric SAR image classification method

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Embodiment Construction

[0036] The present invention will be further described below in conjunction with the accompanying drawings.

[0037] refer to figure 1 , the concrete steps that the present invention realizes are as follows:

[0038] Step 1, input the coherence matrix of the polarimetric SAR SAR image to be classified.

[0039] Step 2, compensating the polarimetric SAR SAR coherence matrix.

[0040] Take the polarization azimuth angle for the polarization synthetic aperture radar SAR coherence matrix, use the polarization azimuth angle to calculate the rotation matrix of the polarization coherence matrix, use the rotation matrix to perform rotation transformation on the coherence matrix, and obtain the compensated polarization coherence matrix, the specific operation Proceed as follows:

[0041] The first step is to calculate the polarization azimuth angle of the polarization synthetic aperture radar SAR coherence matrix according to the following formula:

[0042]

[0043] Among them, ...

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Abstract

The invention discloses a scattering energy and stack self-code-based polarimetric SAR image classification method, and mainly aims at solving the problems that classification process is complicated,polarimetric SAR image spatial features cannot be extracted and classification precision is not high due to the influences of extraction data independence and redundancy of polarimetric synthetic aperture radar SAR image features in the prior art. The method comprises the following specific realization steps of: (1) inputting a coherence matrix of a to-be-classified polarimetric synthetic apertureradar SAR image; (2) compensating the polarimetric SAR coherence matrix; (3) obtaining scattering energy of a scanning model; (4) obtaining a sample; (5) training stack self-codes; (6) classifying the stack self-codes; and (7) outputting a classification result. The method has the advantage of being remarkable in polarimetric synthetic aperture radar SAR image classification effect.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a polarization synthetic aperture radar (Synthetic Aperture Radar SAR) image classification method based on scattered energy and stack self-encoding in the field of target recognition. The invention can be used for ground object classification and target recognition of polarization synthetic aperture radar SAR images. Background technique [0002] Compared with traditional synthetic aperture radar, polarimetric synthetic aperture radar (SAR) uses the scattering information of multiple channels to obtain a more comprehensive understanding of the target. The classification of polarimetric SAR SAR images is an important research content of polarimetric SAR SAR image interpretation. The classification map can be used as an intermediate result to provide auxiliary information for edge extraction, target detection, recognition, etc., and can also be directly output as th...

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Application Information

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IPC IPC(8): G06K9/62
Inventor 尚荣华刘永坤焦李成刘芳王荣芳马晶晶王爽侯彪
Owner XIDIAN UNIV
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