Multisource classification using ICM and Dempster-Shafer theory

IEEE Transactions on Instrumentation and Measurement

Volumn 51, Issue 2, 2002, Pages 277-281

  Foucher, Samuel ^a,b   Germain, Mickaël ^a,c   Boucher, Jean Marc ^a,c   Bénié, Goze Bertin ^a,b  

^a IEEE   (Canada)

^b UNIVERSITÉ DE SHERBROOKE   (Canada)

^c ECOLE DES MINES DE NANTES   (France)

Author keywords

Data fusion; Dempster Shafer theory; ICM algorithm; Multisource classification; Remote sensing

Indexed keywords

MULTISOURCE CALSSIFICATIONS;

ALGORITHMS; ANNEALING; COMPUTER SIMULATION; MARKOV PROCESSES; RELAXATION PROCESSES; REMOTE SENSING; SENSOR DATA FUSION;

IMAGE PROCESSING;

EID: 0036543797     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/19.997824     Document Type: Article

References (7)

1. On the statistical analysis of dirty pictures
2. Local and global multiscale image classification
3. A k-nearest neigbor classification role based on Dempster-Shafer theory
4. Evidential reasoning approach to multi-source-data classification
5. Application of Demspter-Shafer evidence theory to unsupervised classification in multisource remote sensing
6. Belief function representation of statistical evidence