Method for classifying polarimetric SAR (synthetic aperture radar) images on the basis of Cloude decomposition and K-wishart distribution

Abstract

The invention discloses a method for classifying polarimetric SAR (synthetic aperture radar) images on the basis of Cloude decomposition and K-wishart distribution and mainly solves the problem that the prior art is poor in classification effect and high in computation complexity. The method includes the steps of firstly, reading a polarimetric SAR image to be classified, subjecting each pixel of the image to Cloude decomposition to obtain an entropy H and a scattering angle alpha; secondly, initially partitioning the polarimetric SAR image according to the values of the entropy H and the scattering angle into eight classes; thirdly, subjecting results of eight classes of the whole polarimetric SAR image to iteration to obtain more accurate classification results. Compared with classic classification methods, the method is stricter in partitioning the polarimetric SAR image, better in classification effect, lower in computation complexity and applicable to terrain classification and target recognition of the polarimetric SAR images.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to classification of ground objects in polarimetric synthetic aperture radar (SAR) images, which can be used for classification of ground objects and target recognition in polarimetric SAR images. 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. Compared with SAR, polarimetric SAR performs full polarimetric measurement, which can obtain richer information about the target. In recent years, the classification using polarimetric SAR measurement data has been highly valued in the international remote sensing field, and has become the main research direction of image classification. Classical polarization SAR class...

AI Technical Summary

Problems solved by technology

However, there are two defects in H / α classification: one is that the classification boundary is fixed, which leads to the division of regions too arbitrary; the other is that the number of classification categories is fixed, which lacks flexibility in the classification of complex regions, and the classification accuracy is low.

This algorithm combines Freeman decomposition and complex Wishart distribution, which can maintain the purity of the main scattering mechanism of polarimetric SAR, but due to the division and merging of multiple categories in this method, its computational complexity is relatively high

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