Classification of GF-3 fully polarimetric SAR image combined with the Singh four-component decomposition

doi:10.13474/j.cnki.11-2246.2020.0050

Bulletin of Surveying and Mapping ›› 2020, Vol. 0 ›› Issue (2): 86-89.doi: 10.13474/j.cnki.11-2246.2020.0050

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Classification of GF-3 fully polarimetric SAR image combined with the Singh four-component decomposition

WANG Songsong^1,2, ZHANG Yonghong², KONG Xiangyi^1,2

1. College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China;
2. Chinese Academy of Surveying and Mapping, Beijing 100830, China

Received:2019-06-10 Revised:2019-08-06 Online:2020-02-25 Published:2020-03-04

Abstract

Abstract: Different from general classification algorithm, pixel statistics based classification ignores the scattering characteristics of objects. In this paper, an classification method for preserving the scattering characteristics of objects was proposed. This method combined the Singh four-component decomposition proposed by Singh with the maximum likelihood classifier based on the complex Wishart distribution for classification of GF-3 polarimetric images. Surface scattering, volume scattering, double-bounce scattering and helix scattering were obtained by Singh four-component decomposition, then the first three basic scatterings were divided into multiple clusters respectively, and the inter-class merging was performed according to the complex Wishart distance until the specified number of categories was obtained. The Wishart classifier was used foriterative classification and merged the categories at last to obtain the final classification result. Through experiments, it was proved that the algorithm proposed in this paper had a good classification performance and verified the feasibility of using GF-3 satellite data for image classification.

Key words: PolSAR, polarization decomposition, scattering characteristics, GF-3, land-cover classification

CLC Number:

P237

WANG Songsong, ZHANG Yonghong, KONG Xiangyi. Classification of GF-3 fully polarimetric SAR image combined with the Singh four-component decomposition[J]. Bulletin of Surveying and Mapping, 2020, 0(2): 86-89.

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Classification of GF-3 fully polarimetric SAR image combined with the Singh four-component decomposition

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