Stochastic Geometry for Image Analysis

Inbunden, Engelska, 2011

Av Xavier Descombes, France) Descombes, Xavier (INRIA

1 969 kr

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This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.

Produktinformation

Utgivningsdatum2011-11-25
Mått163 x 240 x 26 mm
Vikt671 g
FormatInbunden
SpråkEngelska
Antal sidor384
FörlagISTE Ltd and John Wiley & Sons Inc
ISBN9781848212404

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Chapter 1. Introduction 1X. DESCOMBESChapter 2. Marked Point Processes for Object Detection 11X. DESCOMBES2.1. Principal definitions 112.2. Density of a point process 152.3. Marked point processes 212.4. Point processes and image analysis 22Chapter 3. Random Sets for Texture Analysis 29C. LANTUÉJOUL and M. SCHMITT3.1. Introduction 293.2. Random sets 333.3. Some geostatistical aspects 423.4. Some morphological aspects 513.5. Appendix: demonstration of Miles’ formulae for the Boolean model 61Chapter 4. Simulation and Optimization 65F. LAFARGE, X. DESCOMBES, E. ZHIZHINA and R. MINLOS4.1. Discrete simulations: Markov chain Monte Carlo algorithms 664.2. Continuous simulations 914.3. Mixed simulations 1054.4. Simulated annealing 106Chapter 5. Parametric Inference for Marked Point Processes in Image Analysis 113R. STOICA, F. CHATELAIN and M. SIGELLE5.1. Introduction 1135.2. First question: what and where are the objects in the image? 1175.3. Second question: what are the parameters of the point process that models the objects observed in the image? 1295.4. Conclusion and perspectives 1585.5. Acknowledgments 159Chapter 6. How to Set Up a Point Process? 161X. DESCOMBES6.1. From disks to polygons, via a discussion of segments 1626.2. From no overlap to alignment 1676.3. From the likelihood to a hypothesis test 1726.4. From Metropolis–Hastings to multiple births and deaths 176Chapter 7. Population Counting 179X. DESCOMBES7.1. Detection of Virchow–Robin spaces 1807.2. Evaluation of forestry resources 1927.3. Counting a population of flamingos 2077.4. Counting the boats at a port 229Chapter 8. Structure Extraction 249F. LAFARGE and X. DESCOMBES8.1. Detection of the road network 2508.2. Extraction of building footprints 2628.3. Representation of natural textures 269Chapter 9. Shape Recognition 287F. LAFARGE and C. MALLET9.1. Modeling of a LIDAR signal 2879.2. 3D reconstruction of buildings 308Bibliography 325List of Authors 341Index 343