Gómez Muñoz, Inés María: Concepts elaboration and system architectures for mining very large image archives. 2009
Inhalt
- Abstract
- Zusammenfassung
- Resumen
- Contents
- List of Figures
- List of Tables
- Introduction
- Overview of Existing Mining Systems
- Image Information Mining System Architecture
- Semantic Learning for Content-based Image Retrieval
- Existing Image Information Mining Systems
- The Knowledge-driven Information Mining System: Concept and Overview
- Basics of Inference and Stochastic Image Analysis
- Stochastic Image Analysis
- Bayesian Inference
- Elements of Information Theory
- Shannon / Differential Entropy
- Kullback Leibler divergence or distance
- Mutual Information
- Cramr-Rao Lower Bound and Fisher Information
- Rate Distortion Theory
- Conclusions
- Earth Observation Image Feature Extraction
- Multi Temporal Analysis of High Resolution Images
- Problem Statement
- State of the art in Multi Temporal Analysis
- Feature Extraction Methods for Target Detection
- Texture Analysis
- Linear Feature Extraction
- Discrete Cosine Transform Based Dimension Reduction
- Conclusions
- Clustering
- Clustering Phase in Information Hierarchy
- K-means: Generalized Lloyd Algorithm
- Dyadic k-means
- Conclusions
- Optimization of Feature Extraction based on Rate Distortion Theory
- Interactive Learning
- Interactive Learning
- Probabilistic Retrieval
- Multiple Classifier
- Human Machine Communication and Relevance Feedback
- Conclusions
- Optimal System Design Approach
- Web Service Technology
- Concept and Design of a Knowledge Centered Earth Observation System
- KEO System Architecture
- Conclusions
- Application Domains
- Multi Temporal Analysis for Target Detection
- Validation of KIM Classification by User-defined Labels
- Conclusions
- Conclusions
- Data Characterization
- Theorems
- Acronyms
- Bibliography
- Acknowledgments