A high-resolution SAR image classification method based on intensity ratio and spatial structure feature extraction

A technology of spatial structure and feature extraction, applied in the field of image processing, can solve the problems of poor regional consistency, messy boundaries, similar inseparable features, etc., to achieve the effect of ensuring integrity

Active Publication Date: 2019-04-16
XIDIAN UNIV
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Problems solved by technology

[0008] The technical problem to be solved by the present invention is to provide a high-resolution SAR image classification method based on intensity ratio and spatial structure feature extraction to sol

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  • A high-resolution SAR image classification method based on intensity ratio and spatial structure feature extraction
  • A high-resolution SAR image classification method based on intensity ratio and spatial structure feature extraction
  • A high-resolution SAR image classification method based on intensity ratio and spatial structure feature extraction

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Embodiment Construction

[0063] The present invention provides a kind of high-resolution SAR image classification method based on intensity ratio and spatial structure feature extraction, carry out boundary extension to the classified SAR image by mirror reflection around the boundary; carry out block extraction to the expanded SAR image I={ I 1 ,I 2 ,...,I N}; Calculate the spatial structure characteristics of the block G={G 1 ,G 2 ,...,G N}; Carry out boundary extension and extraction blocks on the original SAR image again; calculate the intensity ratio feature coefficient H of the block Intensity =[h Intensity (1), h Intensity (2),...,h Intensity (x)]; perform vector superposition on the intensity ratio feature and spatial structure information feature; select some sample points and put them into the SVM classifier to train the model; put the whole image into the model to get the final prediction label map, that is, the final classification Result graph.

[0064] see figure 1 , a kind of h...

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Abstract

The invention discloses a high-resolution SAR (Synthetic Aperture Radar) image classification method based on intensity ratio and spatial structure feature extraction. The method comprises the following steps: performing mirror reflection on a classified SAR image around a boundary to perform boundary expansion; Carrying out block extraction on the extended SAR image; Calculating spatial structurecharacteristics of the block; Performing boundary expansion on the original SAR image again to extract blocks; Calculating an intensity ratio characteristic coefficient of the block; Carrying out vector superposition on the intensity ratio characteristics and the spatial structure information characteristics; Selecting a part of sample points and putting the sample points into an SVM classifier to train a model; And putting the whole image into the model to obtain a final prediction label image as a final classification result image. The method has the advantages that classification is finer,boundaries are more obvious, and region extraction features are easier to be classified, and can be used for SAR image classification and target recognition.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a high-resolution SAR image classification method based on intensity ratio and spatial structure feature extraction. Background technique [0002] In practical applications, it is necessary to use remote sensing satellites to monitor the environment and flood disasters in real time to minimize disaster losses. Synthetic aperture radar (SAR) systems have been widely used in remote sensing applications for many years due to their long-range performance, strong penetration, and all-weather acquisition capabilities. So it is very important to study the classification algorithm of fast, adaptive and high-precision SAR image objects. However, the understanding of SAR data is a long-term and challenging task due to the existence of multiplicative speckle noise. [0003] In the SAR image classification problem, it generally includes two parts: feature extraction an...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/13G06F18/2411G06F18/253
Inventor 侯彪焦李成李琳马晶晶马文萍白静
Owner XIDIAN UNIV
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