INTRODUCTION OF NEIGHBORHOOD INFORMATION IN EVIDENCE THEORY AND APPLICATION TO DATA FUSION OF RADAR AND OPTICAL IMAGES WITH PARTIAL CLOUD COVER
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摘要
Two ways of introducing spatial information in Dempster–Shafer evidence theory are examined: in the definition of the monosource mass functions, and, during data fusion. In the latter case, a “neighborhood” mass function is derived from the label image and combined with the “radiometric” masses, according to the Dempster orthogonal sum. The main advantage of such a combination law is to adapt the importance of neighborhood information to the level of radiometric missing information. The importance of introducing neighborhood information has been illustrated through the following application: forest area detection using radar and optical images showing a partial cloud cover.
论文关键词:Data fusion,Multisource classification,Evidence theory,Missing information,Spatial neighborhood,Remote sensing
论文评审过程:Received 27 October 1997, Accepted 5 March 1998, Available online 7 June 2001.
论文官网地址:https://doi.org/10.1016/S0031-3203(98)00051-X