LEADER 05468nam 2200697Ia 450 001 9910830598303321 005 20170815145448.0 010 $a1-282-16497-X 010 $a9786612164972 010 $a0-470-61107-3 010 $a0-470-39365-3 035 $a(CKB)2550000000005864 035 $a(EBL)477652 035 $a(SSID)ssj0000339029 035 $a(PQKBManifestationID)11252174 035 $a(PQKBTitleCode)TC0000339029 035 $a(PQKBWorkID)10299337 035 $a(PQKB)10949043 035 $a(MiAaPQ)EBC477652 035 $a(CaSebORM)9781848210196 035 $a(OCoLC)520990430 035 $a(PPN)190663286 035 $a(EXLCZ)992550000000005864 100 $a20070501d2008 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aInformation fusion in signal and image processing$b[electronic resource] $emajor probabilistic and non-probabilistic numerical approaches /$fedited by Isabelle Bloch 205 $a1st edition 210 $aLondon $cISTE ;$aHoboken, NJ $cWiley$d2008 215 $a1 online resource (297 p.) 225 1 $aISTE ;$vv.22 300 $a"First published in France in 2003 by Herme?s Science/Lavoisier entitled 'Fusion d'informations en traitement du signal et des images'" --T.p. verso. 311 $a1-84821-019-1 320 $aIncludes bibliographical references and index. 327 $aInformation Fusion in Signal and Image Processing; Table of Contents; Preface; Chapter 1. Definitions; 1.1. Introduction; 1.2. Choosing a definition; 1.3. General characteristics of the data; 1.4. Numerical/symbolic; 1.4.1. Data and information; 1.4.2. Processes; 1.4.3. Representations; 1.5. Fusion systems; 1.6. Fusion in signal and image processing and fusion in other fields; 1.7. Bibliography; Chapter 2. Fusion in Signal Processing; 2.1. Introduction; 2.2. Objectives of fusion in signal processing; 2.2.1. Estimation and calculation of a law a posteriori 327 $a2.2.2. Discriminating between several hypotheses and identifying2.2.3. Controlling and supervising a data fusion chain; 2.3. Problems and specificities of fusion in signal processing; 2.3.1. Dynamic control; 2.3.2. Quality of the information; 2.3.3. Representativeness and accuracy of learning and a priori information; 2.4. Bibliography; Chapter 3. Fusion in Image Processing; 3.1. Objectives of fusion in image processing; 3.2. Fusion situations; 3.3. Data characteristics in image fusion; 3.4. Constraints; 3.5. Numerical and symbolic aspects in image fusion; 3.6. Bibliography 327 $aChapter 4. Fusion in Robotics4.1. The necessity for fusion in robotics; 4.2. Specific features of fusion in robotics; 4.2.1. Constraints on the perception system; 4.2.2. Proprioceptive and exteroceptive sensors; 4.2.3. Interaction with the operator and symbolic interpretation; 4.2.4. Time constraints; 4.3. Characteristics of the data in robotics; 4.3.1. Calibrating and changing the frame of reference; 4.3.2. Types and levels of representation of the environment; 4.4. Data fusion mechanisms; 4.5. Bibliography; Chapter 5. Information and Knowledge Representation in Fusion Problems 327 $a5.1. Introduction5.2. Processing information in fusion; 5.3. Numerical representations of imperfect knowledge; 5.4. Symbolic representation of imperfect knowledge; 5.5. Knowledge-based systems; 5.6. Reasoning modes and inference; 5.7. Bibliography; Chapter 6. Probabilistic and Statistical Methods; 6.1. Introduction and general concepts; 6.2. Information measurements; 6.3. Modeling and estimation; 6.4. Combination in a Bayesian framework; 6.5. Combination as an estimation problem; 6.6. Decision; 6.7. Other methods in detection; 6.8. An example of Bayesian fusion in satellite imagery 327 $a6.9. Probabilistic fusion methods applied to target motion analysis6.9.1. General presentation; 6.9.2. Multi-platform target motion analysis; 6.9.3. Target motion analysis by fusion of active and passive measurements; 6.9.4. Detection of a moving target in a network of sensors; 6.10. Discussion; 6.11. Bibliography; Chapter 7. Belief Function Theory; 7.1. General concept and philosophy of the theory; 7.2. Modeling; 7.3. Estimation of mass functions; 7.3.1. Modification of probabilistic models; 7.3.2. Modification of distance models 327 $a7.3.3. A priori information on composite focal elements (disjunctions) 330 $aThe area of information fusion has grown considerably during the last few years, leading to a rapid and impressive evolution. In such fast-moving times, it is important to take stock of the changes that have occurred. As such, this books offers an overview of the general principles and specificities of information fusion in signal and image processing, as well as covering the main numerical methods (probabilistic approaches, fuzzy sets and possibility theory and belief functions). 410 0$aISTE 606 $aSignal processing 606 $aImage processing 615 0$aSignal processing. 615 0$aImage processing. 676 $a621.382/2 676 $a621.3822 686 $aZN 6025$2rvk 700 $aBloch$b Isabelle$0856054 701 $aBloch$b Isabelle$0856054 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830598303321 996 $aInformation fusion in signal and image processing$94028200 997 $aUNINA