Region graph and statistic similarity coding-based SAR (synthetic aperture radar) image segmentation method

Abstract

The invention discloses an region graph and statistic similarity coding-based SAR (synthetic aperture radar) image segmentation method. The problem that characteristics of an image are required to be manually extracted by experience in the prior art is mainly solved. The method is implemented by the following steps: 1, extracting a sketch map according to an SAR image sketch model, and completing the sketch map; 2, extracting an region graph according to the completed sketch map; 3, training a stacked noise reduction auto-coding network of each sub-region of which the pixel number is more than a threshold value in a concentrated region and a homogenous region; 4, performing structural characteristic coding on the network of each sub-region of the concentrated region and the homogenous region to obtain a structural characteristic expression of each sub-region; 6, performing hierarchical clustering on the concentrated region and the homogenous region to obtain segmentation results of the concentrated region and the homogenous region respectively; 6, segmenting a structural region to obtain a final SAR image segmentation result by utilizing an average ratio algorithm. According to the method, the segmentation result is higher in region consistency, ground object distinguishing effects are improved, and the method can be used for target detection and identification.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a SAR image segmentation method, which can be used for subsequent target detection and recognition. Background technique [0002] The so-called image segmentation refers to dividing the image into several non-overlapping regions according to features such as gray scale, color, texture and shape, and making these features show similarities in the same region, but show obvious differences between different regions. process of difference. The purpose of image segmentation is to simplify or change the representation of the image, making the image easier to understand and analyze. In general, autonomous segmentation is one of the most difficult tasks in image processing. Image segmentation is the basis of image understanding and interpretation, and the quality of image segmentation directly affects subsequent analysis and recognition. In general, the more accur...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to address the deficiencies of the above-mentioned existing methods, and propose a SAR image segmentation method based on region maps and statistical similarity coding, to solve the problem that traditional SAR image segmentation methods need to rely on manual experience to extract image features, and improve Distinguishing effect of ground objects in SAR images

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