1. Enhanced Hexagonal Search for Fast Block Motion Estimation Authors ： Ce Zhu, Xiao Lin, Lappui Chau, and Lai-Man Po Lappui Chau, and Lai-Man Po IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, OCTOBER 2004

2. Outline Introduction Introduction HEXBS ( Hexagon-Based Search ) HEXBS ( Hexagon-Based Search ) Predictive HEXBS Predictive HEXBS Fast Hexagonal Inner Search Fast Hexagonal Inner Search 6-Side-Based Fast Inner Search 6-Side-Based Fast Inner Search Enhanced HEXBS Algorithm Enhanced HEXBS Algorithm Experimental Results And Analysis Experimental Results And Analysis Conclusion Conclusion

3. Introduction Fast block motion estimation process ： Fast block motion estimation process ： STEP 1 ： low-resolution coarse search STEP 1 ： low-resolution coarse search → To identify a small area where the → To identify a small area where the best motion vector is expected to lie best motion vector is expected to lie STEP 2 ： fine-resolution inner search STEP 2 ： fine-resolution inner search → To select the best motion vector in → To select the best motion vector in the located small region the located small region

4. Most motion estimation algorithms attempt to speed up the coarse search without considering accelerating the inner search Most motion estimation algorithms attempt to speed up the coarse search without considering accelerating the inner search Enhanced hexagonal search algorithm is proposed to improve the performance ： Enhanced hexagonal search algorithm is proposed to improve the performance ： (1) Reducing number of search points (1) Reducing number of search points (2) Decrease the distortion (2) Decrease the distortion Introduction

5. The two-dimensional logarithmic search The two-dimensional logarithmic search Three-step search (TSS) Three-step search (TSS) New three-step search (NTSS) New three-step search (NTSS) Four-step search (4SS) Four-step search (4SS) Block-based gradient descent search (BBGDS) Block-based gradient descent search (BBGDS) Simple and efficient search (SES) Simple and efficient search (SES) Diamond search (DS) Diamond search (DS) The hexagonal search The hexagonal search Hexagon-based search (HEXBS) Hexagon-based search (HEXBS) Enhanced hexagon-based search Enhanced hexagon-based searchIntroduction

6. HEXBS

7. Inner points in the hexagonal search pattern HEXBS

8. Using the shrunk hexagonal pattern covering the points 2, 4, 5, and 7 Using the shrunk hexagonal pattern covering the points 2, 4, 5, and 7 A gradient scheme ： A gradient scheme ： Ex ： Points 1 and 3 if point 2 wins in the last step Ex ： Points 1 and 3 if point 2 wins in the last step of the HEXBS algorithm of the HEXBS algorithm The inner search for the HEXBS

9. The flowchart of HEXBS NHEXBS (mx, my) = 7 + 3n + 4 where n is the number of times of low-resolution coarse search

10. Predictive HEXBS The error distortion function has monotonic characteristic in a localized search area The error distortion function has monotonic characteristic in a localized search area The motion vector of the current block is highly correlated to those of its neighboring blocks. The motion vector of the current block is highly correlated to those of its neighboring blocks. The motion information of neighboring blocks can be utilized for prediction of a good starting point The motion information of neighboring blocks can be utilized for prediction of a good starting point

11. Consider the upper and the left neighboring blocks Consider the upper and the left neighboring blocks Finding a good starting point using the neighboring motion vectors Finding a good starting point using the neighboring motion vectors Normally finds better motion vectors than the original HEXBS scheme Normally finds better motion vectors than the original HEXBS scheme Predictive HEXBS

12. Not a full inner search, only check a portion of the inner search points Not a full inner search, only check a portion of the inner search points Strong correlation exists between the inner search points Strong correlation exists between the inner search points Based on the monotonic distortion characteristic in the localized area around the global minimum Based on the monotonic distortion characteristic in the localized area around the global minimum Fast Hexagonal Inner Search

13. Group the search points in the six sides of the hexagon Group the search points in the six sides of the hexagon Define a group distortion by summing the distortions of all the points within the group Define a group distortion by summing the distortions of all the points within the group We focus the inner search just in the region near to the group with the smallest group distortion We focus the inner search just in the region near to the group with the smallest group distortion For different groups (sides) in different locations, we have different number of inner search points For different groups (sides) in different locations, we have different number of inner search points 6-Side-Based Fast Inner Search

15. HEXBS incorporate the 6-side-based fast inner search scheme HEXBS incorporate the 6-side-based fast inner search scheme Moreover, incorporate the Predictive HEXBS Moreover, incorporate the Predictive HEXBS The reduction of number of search points for the enhanced HEXBS algorithm ： The reduction of number of search points for the enhanced HEXBS algorithm ： (1) The prediction for a good starting point (1) The prediction for a good starting point using the predictive HEXBS, using the predictive HEXBS, (2) The fast inner search. (2) The fast inner search. Enhanced HEXBS Algorithm

16. Experimental Results And Analysis

17. TABLE III, where Ni is the number of search points used in the Method i,where MSEi is the distortions for Methods i

20. Conclusion Enhanced HEXBS speeds up the motion estimation and decreases distortions Enhanced HEXBS speeds up the motion estimation and decreases distortions Only part of the inner points will be evaluated Only part of the inner points will be evaluated Enhanced HEXBS algorithm outperforms the original HEXBS Enhanced HEXBS algorithm outperforms the original HEXBS