Introduction of neighborhood information in evidence theory and application to data fusion of radar and optical images with partial cloud cover

Abstract 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.