Amankwah, Anthony: Image registration via entropy consideration and data fusion. 2008
Inhalt
- CONTENTS
- ZUSAMMENFASSUNG
- ABSTRACT
- ACKNOWLEDGEMENTS
- 1 INTRODUCTION
- 1.1 Introduction
- 1.2 Image registration methods
- 1.3 Transformations
- 1.4 Robust and efficient image registration methods
- 1.5 Problem definition and goals
- 1.6 Overview of thesis
- 2 RELATED WORK
- 2.1 Elements of image registration
- 2.2 Similarity metrics
- 2.3 Search Data Strategies
- 2.4 Search space strategies
- 2.5 Feature-based methods
- 2.6 Estimation of the mapping function
- 2.7 Image resampling
- 2.8 Registration quality estimation
- 3 AUTOMATIC SUBIMAGE MATCHING
- 3.1 Advantages of template matching
- 3.2 Automatic subimage selection
- 3.3 Experiment and results
- 3.4 Discussion and Analysis
- 3.5 The Sharpness of MI curves for different features
- 3.6 Reliability of similarity measures
- 3.7 Summary
- 4 ENTROPY-BASED SIMILARITY METRICS FOR IMAGE REGISTRATION
- 4.1 Basic Statistics
- 4.2 Entropy and maximum likelihood
- 4.3 F-divergence
- 4.4 F-information
- 4.5 Concept of mutual information
- 4.6 Properties of mutual information
- 4.7 Estimation of probability density function
- 4.8 Concept of feature space
- 4.9 Effect of bin size for mutual information computation
- 4.10 Gradient-based search space strategy
- 4.11 Summary
- 5 IMAGE REGISTRATION USING A COMBINATION OFMUTUAL INFORMATION AND SPATIAL INFORMATION
- 5.1 Quantitative and qualitative information
- 5.2 Quantitative and a qualitative relative information
- 5.3. Spatial mutual information
- 5.4 Utility of pixels
- 5.5 Experiments
- 5.6 Summary
- 6 REGISTRATION TEST IMAGES
- 7 CONCLUSIONS
- REFERNCES
- Appendix