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SAR image segmentation method based on sar-kaze feature extraction

A technology of feature extraction and image segmentation, applied in the field of image processing, can solve the problems of missing some edges and details, and high complexity, and achieve the effect of reducing the complexity of segmentation

Active Publication Date: 2019-10-11
XIDIAN UNIV
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Problems solved by technology

However, the disadvantage of this method is that this method uses the SIFT feature of the SAR image, and the SIFT algorithm establishes a linear scale space and loses some edges and details in the image; this method requires training for the three-layer RBM, high complexity

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  • SAR image segmentation method based on sar-kaze feature extraction

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Embodiment Construction

[0027] refer to figure 1 , the implementation steps of the present invention are as follows:

[0028] Step 1, input a SAR image and transform it into a double precision matrix.

[0029] Read in a SAR image with a size of D*N in the simulation software MATLAB to obtain the grayscale matrix of the original SAR image, and use the double function in MATLAB to convert each integer element value of the grayscale matrix into a double-precision element value , to get the double-precision matrix I, where D>0, N>0.

[0030] Step 2, perform image expansion on the double-precision matrix I.

[0031] Existing image boundary extension methods include image boundary repetition, outer packaging, adding constants and mirror image extension methods, which are used in the present invention but are not limited to the mirror image extension method of images, which are implemented as follows:

[0032] Set the extension value p to an odd number greater than 1, take the leftmost column vector of t...

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Abstract

The invention discloses a SAR image segmentation method based on SAR-KAZE feature extraction, which mainly solves the problems of low accuracy and efficiency of SAR image segmentation in the prior art. The segmentation process is as follows: 1) Input an original SAR image to be segmented and perform double-precision conversion on it; 2) Perform mirror expansion and block segmentation on the double-precision matrix to obtain image blocks of the double-precision matrix; 4) Carry out image blocks on the image block The KAZE feature extraction of the SAR image obtains the SAR-KAZE feature matrix X of the double-precision matrix; 5) The improved sparse subspace clustering is used to cluster the SAR-KAZE feature matrix X to obtain the clustering result of the double-precision matrix. The SAR-KAZE feature extracted by the present invention retains more image edge and detail information, improves segmentation accuracy, uses improved sparse subspace clustering to cluster images, reduces segmentation complexity, and can be used for ground objects in radar imaging Classification of the target.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a SAR image segmentation method, which can be used for the classification of ground objects in radar imaging. Background technique [0002] Synthetic aperture radar is an active earth observation system that can be installed on aircraft, satellites, spacecraft and other flight platforms to observe the earth all day and all weather, and has a certain surface penetration capability. SAR image is a high-resolution image, which has unique advantages in disaster monitoring, environmental monitoring, ocean monitoring, resource exploration, crop yield estimation, surveying and mapping, and military applications, and can play a role that other remote sensing images are difficult to play. [0003] Image feature extraction and matching has always been one of the research hotspots in the field of image processing, and has been widely used in the fields of visual navigation, remote sensing im...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/11G06K9/62
CPCG06T7/11G06T2207/10044G06F18/2136G06F18/23
Inventor 侯彪焦李成刘胜男马晶晶马文萍王爽白静
Owner XIDIAN UNIV