%0 Journal Article %T Recalage et fusion d'images sonar multivues : utilisation du conflit %+ Extraction et Exploitation de l'Information en Environnements Incertains (E3I2) %+ Human-machine spoken dialogue (CORDIAL) %A Rominger, Cédric %A Martin, Arnaud %< avec comité de lecture %@ 1764-1667 %J Revue des Nouvelles Technologies de l'Information %I Editions RNTI %V E %N 21 %P 231-246 %8 2011-02-18 %D 2011 %K belief function %K conflict %K sonar image %Z ACM: I.4, I.5 %Z Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] %Z Computer Science [cs]/Artificial Intelligence [cs.AI] %Z Engineering Sciences [physics]/Signal and Image processing %Z Computer Science [cs]/Signal and Image ProcessingJournal articles %X This paper presents an application for classified image registration and fusion. We extend here results developed on a previous paper to multiview images. For seabed characterization, we need to fuse the multiview of sonar images to increase performances. However, before fusion, we have to proceed to an image registration. The proposed approach is based on the use of the conflict due to the combination as a disimilarity measure in the classified images registration. The theory of belief functions allows an unique framework to model the imperfections and to fuse the classified images. %G French %2 https://hal.science/hal-00657626/document %2 https://hal.science/hal-00657626/file/paperRNTI.pdf %L hal-00657626 %U https://hal.science/hal-00657626 %~ ENSTA-BRETAGNE %~ EC-PARIS %~ UNIV-RENNES1 %~ CNRS %~ INRIA %~ INSA-RENNES %~ ENSSAT %~ INRIA-RENNES %~ IRISA %~ ENSTA-BRETAGNE-STIC %~ IRISA_SET %~ ENSIETA-E3I2 %~ TESTALAIN1 %~ IRISA-D6 %~ INRIA2 %~ UR1-HAL %~ UR1-MATH-STIC %~ UR1-UFR-ISTIC %~ TEST-UNIV-RENNES %~ TEST-UR-CSS %~ UNIV-RENNES %~ INRIA-RENGRE %~ INSA-GROUPE %~ UR1-MATH-NUM