Watershed SAR image segmentation method based on complex wavelet extraction mark

Abstract

The invention discloses a watershed SAR image segmentation method based on complex wavelet extraction mark, which is used for solving the problem of over-segmentation of the watershed SAR image. The invention integrates the advantages of a feature extraction method designated to texture information and of a watershed method on the segmentation of the SAR image, and can excellently inhibit the over-segmentation. The method comprises the specific implementing steps of: (1) obtaining a mark for watershed transform in a manner of complex wavelet energy feature extraction; (2) implementing Gaussian low-pass filter on original images; (3) using Priwitt operator for the filtered images to calculate gradient; (4) correcting the gradient by using inner and outer marks and utilizing a mandatory minimum technology in order that a local minimum area appears at a marked location only; and (5) subjecting the corrected gradient map to the watershed transform to obtain an initial segmentation image of the SAR image. A set of experiments prove that the inventive image segmentation effect accords with the standards basically. The invention not only reduces the over-segmentation, but also guaranteesthe accuracy of edges.

Description

Watershed SAR Image Segmentation Method Based on Complex Wavelet Extraction and Marker technical field The invention belongs to the technical field of image processing, and in particular relates to a watershed SAR image segmentation method based on complex wavelet extraction marks. It is used to suppress over-segmentation of SAR image segmentation in the field of synthetic aperture radar (synthetic aperture radar, SAR) image segmentation. Background technique Synthetic Aperture Radar SAR image segmentation is a key step in automatic processing of SAR images, and its purpose is to segment SAR images into sub-regions or objects with strong correlation. It is convenient for further analysis, recognition, etc. of SAR images, and the accuracy of segmentation directly affects the effectiveness of subsequent tasks. The observation objects of SAR images are ground objects and targets in highly unconstrained scenes. The radar echo is sensitive to the type, orientation, uniformity...

AI Technical Summary

Problems solved by technology

The technical problem to be solved by the present invention is: to overcome the deficiencies of the existing image segmentation technology, that is, the edge of the segmentation result of complex wavelet feature extraction and clustering is not accurate, and the over-segmentation problem of classical watershed transform or marked watershed transform is proposed. A watershed SAR image segmentation method based on complex wavelet extraction marks, using complex wavelet feature extraction and clustering images as the source of watershed marks, combined with a feature extraction method specifically for texture information and a watershed method to segment SAR images, comprehensive The advantages of the two methods eliminate the influence of texture information and effectively solve the over-segmentation problem of watershed SAR image segmentation

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