Remote Sensing Image Fusion : A Practical Guide

**Remote Sensing Image Fusion: A Practical Guide** gives an introduction to remote sensing image fusion providing an overview on the sensors and applications. It describes data selection, application requirements and the choice of a suitable image fusion technique. It comprises a diverse selection of successful image fusion cases that are relevant to other users and other areas of interest around the world. The book helps newcomers to obtain a quick start into the practical value and benefits of multi-sensor image fusion. Experts will find this book useful to obtain an overview on the state of the art and understand current constraints that need to be solved in future research efforts. For industry professionals the book can be a great introduction and basis to understand multisensor remote sensing image exploitation and the development of commercialized image fusion software from a practical perspective. The book concludes with a chapter on current trends and future developments in remote sensing image fusion. Along with the book, RSIF website provides additional up-to-date information in the field. Machine Generated Contents Note: 1. Introduction -- 1.1. Outline Of The Book -- 1.2. Remote Sensing -- 1.3. Multi-sensor Data -- 1.3.1. Optical Remote Sensing -- 1.3.2. Radar Remote Sensing -- 1.3.3. Hyperspectral Remote Sensing -- 1.3.4. Thermal Remote Sensing -- 1.3.5. Lidar -- 1.4. Image And Data Fusion -- 1.4.1. Objectives Of Image Fusion -- 1.4.2. Types Of Fusion -- 1.4.3. Benefits -- 1.4.4. Limitations -- 1.5. Definitions And Terminology For This Book -- 1.5.1. Remote Sensing Images -- 1.5.2. Resolution -- 1.6. Summary -- References -- 2. Fusion Levels -- 2.1. Data Fusion -- 2.2. Fusion In Remote Sensing -- 2.3. Subpixel Level -- 2.4. Pixel Level -- 2.5. Feature Level -- 2.6. Decision Level -- 2.7. Hybrid-level Fusion -- 2.8. Summary -- References -- 3. Preprocessing -- 3.1. Data Selection -- 3.2. General Workflow -- 3.3. Sensor-specific Corrections -- 3.3.1. Radiometric Distortions In Vir Data And Their Corrections -- 3.3.2. Radiometric Corrections Of Sar Images -- 3.3.2.1. Multi-look Processing -- 3.3.2.2. Spatial Averaging Method -- 3.3.2.3. Filtering Techniques -- 3.3.2.4. Antenna Pattern -- 3.3.2.5. 16-bit To 8-bit Data Conversion -- 3.3.2.6. Calibration -- 3.3.3. Geometric Corrections -- 3.3.4. Geometric Distortions In Vir Imagery -- 3.3.5. Geometric Effects In Sar Data -- 3.4. Geometric Corrections -- 3.4.1. Terms -- 3.4.2. Geometric Models -- 3.4.2.1. Polynomial Rectification -- 3.4.2.2. Sensor Model -- 3.4.3. Resampling -- 3.5. Image Enhancement -- 3.5.1. Spatial Filters -- 3.5.2. Frequency Domain -- 3.5.3. Histogram Matching -- 3.6. Summary -- References -- 4. Fusion Techniques -- 4.1. Categorizations Of Image Fusion Techniques -- 4.2. Role Of Color In Image Fusion -- 4.3. Component Substitutions -- 4.3.1. Intensity Hue Saturation Transform -- 4.3.2. Principal Component Substitution -- 4.3.3. Gram-schmidt Transform -- 4.4. Numerical Methods -- 4.4.1. Sum -- 4.4.2. Multiplication -- 4.4.3. Subtractive Resolution Merge And Ratioing -- 4.4.4. Brovey Transform -- 4.4.5. Modulation-based Techniques -- 4.4.6. Color Normalized Spectral Sharpening -- 4.4.7. High-pass Filtering -- 4.5. Statistical Image Fusion -- 4.5.1. Spatially Adaptive Image Fusion -- 4.5.2. Regression Variable Substitution -- 4.5.3. Principal Component Analysis -- 4.5.4. Minimum Mean-square Error Approach -- 4.5.5. Fuzego[TM] -- 4.5.6. Regression Fusion -- 4.6. Multiresolution Approaches -- 4.6.1. Principles -- 4.6.2. Fusion Process -- 4.6.3. Advances In Mra Fusion -- 4.7. Hybrid Techniques -- 4.7.1. Ehlers Fusion -- 4.7.2. Ihs-bt Fusion -- 4.7.3. Wavelet-ihs Fusion -- 4.7.4. Wavelet-pca Fusion -- 4.7.5. Modified Bt-wavelet Fusion -- 4.7.6. Laplacian Filtering And Multiple Regression -- 4.8. Other Fusion Techniques -- 4.8.1. Classification -- 4.8.2. Spatial And Temporal Data Fusion Approaches -- 4.9. Selection Approach -- 4.9.1. Vir/sar -- 4.9.2. Feature Extraction -- 4.9.3. Optimum Index Factor -- 4.10. Comparison And Popularity Of Fusion Techniques -- 4.11. Summary -- References -- 5. Quality Assessment -- 5.1. Overview -- 5.2. Image Quality Parameters -- 5.3. Acceptable Quality Measures In Rsif -- 5.3.1. Mean Bias -- 5.3.2. Mean Square Error -- 5.3.3. Root Mean Square Error -- 5.3.4. Normalized Root Mean Square Error -- 5.3.5. Correlation Coefficient -- 5.3.6. Universal Image Quality Index -- 5.3.7. Uiqi For Four Band Imagery -- 5.3.8. Spectral Angle Mapper -- 5.3.9. Relative Average Spectral Error -- 5.3.10. Relative Dimensionless Global Error Of Synthesis -- 5.3.11. Structure Similarity Index Metric -- 5.4. Rsif Quality Assessment Protocols -- 5.4.1. Wald's Protocol -- 5.4.2. Zhou's Protocol -- 5.4.3. Quality With No Reference Protocol -- 5.4.4. Khan's Protocol -- 5.5. Palubinskas' Generic Framework For Pansharpening Quality Assessment -- 5.6. Value And Requirements For Visual Evaluation -- 5.7. Summary -- References -- 6. Applications -- 6.1. Urban Studies -- 6.1.1. Global Urban Extent Mapping -- 6.1.2. Local Urban Mapping -- 6.1.3. Outlook -- 6.2. Agriculture -- 6.2.1. Mapping Growth Cycles, Plant Health, And Cropland Extent -- 6.2.2. Yield Prediction -- 6.3. Land Use/land Cover Mapping -- 6.4. Change Detection -- 6.4.1. Fusion Techniques In Change Detection -- 6.4.2. Examples Of Change Detection -- 6.5. Geology -- 6.6. Vegetation Monitoring -- 6.6.1. Spatial And Temporal Data Fusion Approach -- 6.6.2. Multimodal Classification -- 6.7. Forest Monitoring -- 6.8. Natural Hazards And Disasters -- 6.8.1. Floods -- 6.8.2. Volcano Eruptions -- 6.8.3. Landslides -- 6.9. Coastal Zone Monitoring -- 6.10. Coal Fire Monitoring -- 6.11. Detection Of Landmines And Minefields -- 6.12. Oceanography -- 6.13. Security And Defense -- 6.14. Missing Information Reconstruction -- 6.15. Other Applications -- 6.16. Summary -- References -- 7. Conclusions And Trends -- 7.1. Challenges -- 7.2. Trends -- 7.3. Data Mining -- 7.4. Cloud Computing -- 7.5. Big Data -- 7.6. Internet Of Things -- 7.7. Summary -- References. Christine Pohl, John Van Genderen. Includes Bibliographical References And Index.