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

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...

AI Technical Summary

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 solve the problem of traditional spatial structure feature analysis applied to SAR image classification prone areas. Poor consistency, messy boundaries, similar and inseparable features before the category

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