Change Detection and Image Time-Series Analysis 1

Summary of Volume 2

Preface

Abdourrahmane M. ATTO, Francesca BOVOLO and Lorenzo BRUZZONE

List of Notations

Chapter 1. Hierarchical Markov Random Fields for High Resolution Land Cover Classification of Multisensor and Multiresolution Image Time Series

Ihsen HEDHLI, Gabriele MOSER, Sebastiano B. SERPICO and Josiane ZERUBIA

1. 1.1. Introduction
   1. 1.1.1. The role of multisensor data in time series classification
   2. 1.1.2. Multisensor and multiresolution classification
   3. 1.1.3. Previous work
2. 1.2. Methodology
   1. 1.2.1. Overview of the proposed approaches
   2. 1.2.2. Hierarchical model associated with the first proposed method
   3. 1.2.3. Hierarchical model associated with the second proposed method
   4. 1.2.4. Multisensor hierarchical MPM inference
   5. 1.2.5. Probability density estimation through finite mixtures
3. 1.3. Examples of experimental results
   1. 1.3.1. Results of the first method
   2. 1.3.2. Results of the second method
4. 1.4. Conclusion
5. 1.5. Acknowledgments
6. 1.6. References

Chapter 2. Pixel-based Classification Techniques for Satellite Image Time Series

Charlotte PELLETIER and Silvia VALERO

1. 2.1. Introduction
2. 2.2. Basic concepts in supervised remote sensing classification
   1. 2.2.1. Preparing data before it is fed into classification algorithms
   2. 2.2.2. Key considerations when training supervised classifiers
   3. 2.2.3. Performance evaluation of supervised classifiers
3. 2.3. Traditional classification algorithms
   1. 2.3.1. Support vector machines
   2. 2.3.2. Random forests
   3. 2.3.3. k-nearest neighbor
4. 2.4. Classification strategies ...