SAR image segmentation method based on high-order multi-scale CRF semi-supervision

An image segmentation and multi-scale technology, applied in the field of image processing, can solve the problems that it is difficult to deal with only a small amount of training data, and the accuracy of segmenting synthetic aperture radar SAR images is not high, so as to achieve the effect of improving accuracy and reducing requirements

Active Publication Date: 2019-02-15
XIDIAN UNIV
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Problems solved by technology

The disadvantage of this method is that the accuracy of segmenting synthetic aperture radar SAR images is not high
The disadvantage of this method is that this method requires a large amount of training data to learn the parameters of the deconvolution network, which is limited to the processing of supervised SAR image segmentation, and it is difficult to deal with the problem of only a small amount of training data in practical applications. situation

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  • SAR image segmentation method based on high-order multi-scale CRF semi-supervision
  • SAR image segmentation method based on high-order multi-scale CRF semi-supervision
  • SAR image segmentation method based on high-order multi-scale CRF semi-supervision

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[0038] The present invention will be further described below in conjunction with the accompanying drawings.

[0039] refer to figure 1 , to further describe the specific implementation steps of the present invention.

[0040] Step 1, input synthetic aperture radar SAR image.

[0041] Step 2: Perform wavelet transform on the input synthetic aperture radar SAR image.

[0042] Step 3, obtain the eigenvector of the high-order multi-scale conditional random field CRF.

[0043] Using the exponential weighted average ratio operator, the image after wavelet transformation is calculated, and the edge strength between each pixel point in each scale and each pixel point in its neighborhood system is calculated.

[0044] The formula of the exponentially weighted average ratio operator is as follows:

[0045]

[0046] in, Indicates the edge strength between the sth pixel in the nth scale of the multi-scale synthetic aperture radar SAR image and the tth pixel in its neighborhood sy...

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Abstract

An SAR image segmentation method of high-order multi-scale CRF semi-supervision is proposed. The method comprises the following steps of (1) inputting an SAR image; (2) carrying out the wavelet transform on the image; (3) obtaining the eigenvectors of a high-order multi-scale CRF; (4) obtaining the local conditional probabilities of the high-order multi-scale CRF; (5) carrying out the initial segmentation of the SAR images; (6) calculating the edge probability of each pixel point; (7) calculating the joint posterior edge probability of each pixel point; (8) calculating a posterior edge probability of each pixel point; (9) segmenting the SAR images; (10) ending segmentation. By taking into account the high-order potential energy and the inter-scale potential energy of each pixel point whencalculating the posterior edge probability, the method of the invention fully utilizes the spatial context structure information and improves the accuracy of the segmentation result.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a synthetic aperture radar SAR (Synthetic Aperture Radar) image segmentation method based on high-order multi-scale CRF (Conditional Random Fields) semi-supervised in the technical field of radar image processing. The invention can be used for segmenting and processing synthetic aperture radar SAR images. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution imaging radar. Its use in civilian and military applications requires the support of synthetic aperture radar SAR image interpretation technology. Synthetic aperture radar SAR image segmentation is an important part of synthetic aperture radar SAR image interpretation technology, which can provide the overall structure of synthetic aperture radar SAR image Therefore, it promotes the application of synthetic aperture radar SAR system in many fields, such as geological exploration and...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/10G06T7/13
CPCG06T2207/10044G06T2207/20064G06T7/10G06T7/13
Inventor 张鹏江银银李明宋婉莹谭啸峰
Owner XIDIAN UNIV
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