Table of Contents
- Foreword
- Preface
- Acknowledgments
- Authors
- Acronyms
- Introduction
- Outline of the Book
- Remote Sensing
- Multi-Sensor Data
- Image and Data Fusion
- Definitions and Terminology for This Book
- Summary
- Fusion Levels
- Data Fusion
- Fusion in Remote Sensing
- Sub-Pixel Level
- Pixel Level
- Feature Level
- Decision Level
- Hybrid-Level Fusion
- Summary
- Preprocessing
- Data Selection
- General Workflow
- Sensor-Specific Corrections
- Geometric Corrections
- Image Enhancement
- Summary
- Fusion Techniques
- Categorizations of Image Fusion Techniques
- Role of Color in Image Fusion
- Component Substitutions
- Numerical Methods
- Statistical Image Fusion
- Multi-Resolution Approaches
- Hybrid Techniques
- Other Fusion Techniques
- Selection Approach
- Conclusions
- Summary
- Quality Assessment
- Overview
- Image Quality Parameters
- Acceptable Quality Measures in RSIF
- RSIF Quality Assessment Protocols
- Palubinskas’ Generic Framework for Pansharpening Quality Assessment
- Value and Requirements for Visual Evaluation
- Summary
- Applications
- Urban Studies
- Agriculture
- Land Use/Land Cover Mapping
- Change Detection
- Geology
- Vegetation Monitoring
- Forest Monitoring
- Natural Hazards and Disasters
- Coastal Zone Monitoring
- Coal Fire Monitoring
- Detection of Landmines and Minefields
- Oceanography
- Security and Defense
- Missing Information Reconstruction
- Other Applications
- Summary
- Conclusions and Trends
- Challenges
- Trends
- Data Mining
- Cloud Computing
- Big Data
- Internet of Things
- Summary
- Index