Polarization synthetic aperture radar (SAR) image classification method based on spectral clustering

Abstract

The invention discloses a polarization synthetic aperture radar (SAR) image classification method based on spectral clustering. The polarization SAR image classification method mainly solves the problem that an existing non-supervision polarization SAR classification method is low in accuracy. The polarization SAR image classification method comprises the steps of extracting scattering entropy H of representation polarization SAR target characteristics to serve as an input characteristic space of a Mean Shift algorithm combining with space coordination information; diving in the characteristic space with the Mean Shift algorithm to obtain M areas; choosing representation points of all areas on the M areas to serve as spectral clustering input to spectrally divide all areas, and further finishing spectral clustering on all pixel points to obtain pre-classification results; and finally classifying the whole image obtained from the pre classification with a Wishart classifier capable of reflecting polarization SAR distribution characteristics in an iteration mode to obtain classification results. Tests show that the polarization SAR image classification method is good in image classification effect and can be applied to non-supervision classification on various polarization SAR images.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to the application in the field of classification of polarimetric SAR images, in particular to a method for classifying polarimetric SAR images based on a spectral clustering algorithm, which can be used for classification of polarimetric SAR images and target recognition. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution active microwave remote sensing imaging radar, which has the advantages of all-weather, all-time, high resolution, and side-view imaging. It can be used in military affairs, agriculture, navigation, geographic surveillance, etc. field. Polarization SAR can obtain the polarization scattering matrix of the scene target by adjusting the polarization mode of sending and receiving electromagnetic waves. Since the polarization scattering matrix contains rich ground object information, it provides an important basis for more in-dept...

AI Technical Summary

Problems solved by technology

One of the shortcomings of H / α classification is that the division of regions is too arbitrary. When the data of the same class is distributed on the boundaries of two or more classes, the performance of the classifier will deteriorate. Another shortcoming is that when the data coexist in the same area When there are several different ground features, it will not be able to effectively distinguish

However, when the algorithm is applied to the field of image segmentation, the amount of calculation and storage is unbearable, which seriously hinders the performance of the algorithm.

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