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结合KI准则和逆高斯模型的SAR影像非监督变化检测
引用本文:庄会富,邓喀中,余美,范洪冬.结合KI准则和逆高斯模型的SAR影像非监督变化检测[J].武汉大学学报(信息科学版),2018,43(2):282-288.
作者姓名:庄会富  邓喀中  余美  范洪冬
作者单位:1.中国矿业大学江苏省资源环境信息工程重点实验室, 江苏 徐州, 221116
基金项目:国家自然科学基金51774270地质灾害防治与地质环境保护国家重点实验室开放基金SKLGP2016K008
摘    要:提出一种结合逆高斯模型(inverse Gaussian model,IGM)和KI(Kittler-Illingworth,KI)最小错误率准则的合成孔径雷达(synthetic aperture radar,SAR)影像非监督变化检测方法。假设差值影像中未变化类和变化类服从混合IGM,结合贝叶斯决策理论,自动求取满足KI最小错误率准则的阈值。在两组多时相SAR数据上分别设计了两组实验以验证本文方法的有效性。实验表明,本文方法可以更好地估计差值影像中未变化类和变化类的概率密度分布,得到合理的决策阈值,有效提高变化检测图的精度。

关 键 词:合成孔径雷达    KI准则    逆高斯模型    贝叶斯决策    阈值选择    变化检测
收稿时间:2016-05-23

A Novel Approach Combining KI Criterion and Inverse Gaussian Model to Unsupervised Change Detection in SAR Images
Institution:1.Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, China2.State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China
Abstract:In this context, a novel approach combining inverse Gaussian model (IGM) and the Kittler-Illingworth (KI) criterion has been proposed to carry out tunsupervised change detection in synthetic aperture radar (SAR) images. The minimum error threshold could be computed by exploiting the Bayes decision theory under the assumption that hybrid IGM could describe the distribution of the changed and unchanged class in difference image. Experiments carried out on two sets of multi-temporal SAR images indicate that the proposed approach can effectively estimate the probability density function of the unchanged and changed classes in the difference image and acquire a reasonable threshold for yielding a better change map from the difference image.
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