高斯Copula的多光谱遥感影像分割

doi:10.16451/j.cnki.issn1003-6059.201907007

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Abstract

To take full advantage of inter-band correlations of multispectral remote sensing images, a multispectral remote sensing image segmentation method based on Gaussian copula function is proposed. Firstly, the Markov random field model is exploited to establish a label field and the label field is characterized by the Potts model. Then, the feature field characterizing pixel spectral measurements is built. A multivariate statistical model based on Gaussian copula modeling pixel spectral measurement is proposed. Furthermore, a posterior probability model of multispectral remote sensing image segmentation is established by Bayes theorem combined with the label field model, the feature field model and the prior probabilities of model parameters. The Metropolis-Hastings algorithm is designed to simulate the posterior probability model, and the optimal segmentation is obtained under the maximum a posterior strategy. Experiments are carried out with simulated and real multispectral images respectively, and experimental results indicate that the proposed algorithm has a strong ability to describe the correlation between bands with a high accuracy.

Key words： Gaussian Copula Remote Sensing Image Segmentation Markov Random Field(MRF) Metropolis-Hastings(M-H) algorithm

Received: 05 March 2019

ZTFLH:

TP 391

Fund:

Supported by Young Scientists Fund of National Natural Science Foundation of China(No.41301479), University Innovation Ta-lent Support Program of Liaoning Province(No.LR2016061),General Project of Science and Technology Research of Liaoning Provincial Education Department(No.LJCL009)

About author:: ZHAO Quanhua(Corresponding author), Ph.D., professor. Her research interests include modeling and analysis of remote sensing image, and application of random geometry in remote sensing image processing.ZHAO Jing, master student. Her research interests include remote sensing image processing.ZHANG Hongyun, Ph.D. candidate. Her research interests include digital image processing.LI Yu, Ph.D., professor. His research interests include remote sensing data processing theory and basic application research.

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	ZHAO Quanhua
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Cite this article:

ZHAO Quanhua,ZHAO Jing,ZHANG Hongyun等. Multispectral Remote Sensing Image Segmentation Using Gaussian Copula[J]. , 2019, 32(7): 633-641.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201907007 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2019/V32/I7/633

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