Synthetic aperture radar image segmentation method based on shear wave hidden Markov model

Abstract

The invention discloses an SAR image segmentation method on the basis of the HMT model in the Shearlet domain, which pertains to the technical field of image processing and mainly aims at solving the problem that the application of the traditional multi-scale geometrical analysis in SAR image segmentation is easy to result in poor regional uniformity and disorder edges. The segmentation process comprises the steps of extracting feature areas (I0, I1, and the like, and IC) in the SAR image to be segmented, calculating the Shearlet transformation coefficients (S0, S1, and the like, and SC) of the feature areas, utilizing the EM algorithm to obtain the HMT model parameter set (Theta1, Theta2, and the like, and ThetaC) in the Shearlet domain of various feature areas, carrying out Shearlet transformation to the SAR image to be segmented to obtain an image coefficient S, utilizing the feature coefficients (S0, S1, and the like, and SC) to calculate likelihood values (Lhood, Lhood, and the like, and Lhood) corresponding to the SAR image coefficient S in each scale, calculating initial segmentation results (MLseg, MLseg, and the like, and MLseg) of the likelihood values in each scale according to the maximum likelihood rule, carrying out fusion to the initial segmentation results by maximizing a posteriori probability criterion and taking the fused image of the scale at the first level as a final segmentation result. The method has the advantages of high convergence rate, good regional uniformity of segmentation result and completely retained information, and can be applied to SAR image target identification.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to a method for SAR image segmentation, which can be applied to target recognition. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution radar system that can be used in many fields such as military affairs, agriculture, navigation, and geographic surveillance. It has many differences compared with other remote sensing imaging systems and optical imaging systems. In terms of military target recognition, SAR images are widely used in the field of target detection, and SAR image segmentation is an important step from image processing to image analysis, and is the basis of target classification and recognition. Essentially, SAR images reflect the electromagnetic scattering and structural characteristics of targets, and their imaging effects largely depend on radar parameters and regional electromagnetic parameters. The particularity of SAR imaging makes th...

AI Technical Summary

Problems solved by technology

The limited directionality of wavelet transform means that some image detail information and edges are lost during the segmentation process, which leads to mis-segmentation and unsatisfactory regional consistency of the wavelet HMTseg method for SAR images containing complex textures.

Since the Contourlet transform has constraints on the number of image directional transformations, it is difficult to establish a neatly corresponding Contourlet domain HMT model, so that the segmentation results have information loss on the details of the SAR image, and the direction information such as boundaries and edges is incomplete.

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