ABSTRACT
List of Tables
Table of Figures
1. Introduction
2. Background and Literature Review
2.1 Category 1: Partial-Search-Set Techniques
2.1.1 Gradient descent techniques using pixel-by-pixel search with step size of one
2.1.2 Gradient descent techniques using coarse-to-fine search
2.1.3 Techniques that search locally according to the predicted motion vector
2.2 Category 2: Partial-Matching-Error Techniques
2.2.1 Techniques which sub-sample the pixels in the target and search blocks
2.2.2 Partial matching error methods
2.2.3 Partial matching error methods using inequalities
2.3 Category 3: Hybrid Techniques
3. Lower bound comparison algorithm
3.1 Theory
3.2 Application Issues
3.2.1 Use of Other Lower Bound Lists
3.2.2LowerboundcomparisonandThree-StepSearchAlgorithmsCombined
4. Implementation and Experiments
4.1 Implementation and execution environment
4.2 Testing Results and Discussions
5. Conclusions
Acknowledgements
References
Appendix Ⅰ
Appendix Ⅱ
