Two-stage clustering-based SAR image semantic segmentation method

Abstract

The invention discloses a two-stage clustering-based SAR image semantic segmentation method, and mainly solves the problem of inaccurate SAR image segmentation in the prior art. The method comprises the following steps of 1) extracting a sketch chart according to a sketch model of an SAR image; 2) regionalizing the sketch chart to obtain a regional chart, and dividing the SAR image into a mixed aggregation structure ground object pixel subspace, a structure pixel subspace and a homogeneous pixel subspace according to the regional chart; 3) designing a directional statistics vector of an extremely non-homogeneous region in the mixed aggregation structure ground object pixel subspace; 4) performing segmentation on the mixed aggregation structure ground object pixel subspace according to the directional statistics vector; 5) performing corresponding segmentation on the structure pixel subspace and the homogeneous pixel subspace in sequence; and 6) combining segmentation results of the three subspaces to obtain a final segmentation result of the SAR image. According to the method, a good segmentation effect of the SAR image can be obtained; and the method can be used for target classification and image interpretation.

Description

Technical field [0001] The invention belongs to the technical field of image processing, and particularly relates to a synthetic aperture radar SAR image segmentation method, which can be applied to target detection, target classification, target positioning, target recognition and image interpretation. Background technique [0002] Synthetic Aperture Radar SAR is particularly suitable for large-area landmark imaging. It can penetrate clouds, fog, rain and snow, and has the ability to work all-weather. With the rapid development of SAR image technology, more and more SAR image data have been obtained, and the automatic interpretation of SAR images by computers has become an urgent problem. SAR image segmentation is the premise of SAR image interpretation, and the result of segmentation directly affects the result of SAR image processing. [0003] In the SAR imaging process, the position of the target is recorded and imaged according to the time sequence of the radar flight in the ...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that when comparing and inferring the structural features of the disconnected regions in the aggregation region, this method uses the reasoning method of the self-organizing feature map SOM network, which needs to be manually determined. The number of clusters, and the clustering time is long, resulting in a decrease in clustering accuracy and affecting the accuracy of SAR image segmentation

The disadvantage of this method is that the pixel-level features of the SAR image are used to extract the features of the SAR image, and the unique structural features of the SAR image due to the correlation between pixels are not learned, resulting in inaccurate segmentation results.

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