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

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. (C) 1998 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.