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Enhanced Hexagonal Search for Fast Block Motion Estimation. Authors : Ce Zhu, Xiao Lin, Lappui Chau, and Lai-Man Po IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, OCTOBER 2004. Outline. Introduction HEXBS ( Hexagon-Based Search ) Predictive HEXBS
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Enhanced Hexagonal Search for Fast Block Motion Estimation Authors:Ce Zhu, Xiao Lin, Lappui Chau, and Lai-Man Po IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, OCTOBER 2004
Outline • Introduction • HEXBS ( Hexagon-Based Search ) • Predictive HEXBS • Fast Hexagonal Inner Search • 6-Side-Based Fast Inner Search • Enhanced HEXBS Algorithm • Experimental Results And Analysis • Conclusion
Introduction • Fastblock motion estimation process : STEP 1:low-resolution coarse search → To identify a small area where the best motion vector is expected to lie STEP 2:fine-resolution inner search → To select the best motion vector in the located small region
Introduction • 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: (1) Reducing number of search points (2) Decrease the distortion
Introduction • The two-dimensional logarithmic search • Three-step search (TSS) • New three-step search (NTSS) • Four-step search (4SS) • Block-based gradient descent search (BBGDS) • Simple and efficient search (SES) • Diamond search (DS) • The hexagonal search • Hexagon-based search (HEXBS) • Enhanced hexagon-based search
HEXBS Inner points in the hexagonal search pattern
The inner search for the HEXBS • Using the shrunk hexagonal pattern covering the points 2, 4, 5, and 7 • A gradient scheme: Ex:Points 1 and 3 if point 2 wins in the last step of the HEXBS algorithm
The flowchart of HEXBS NHEXBS (mx , my) = 7 + 3n + 4 where n is the number of times of low-resolution coarse search
Predictive HEXBS • 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 information of neighboring blocks can be utilized for prediction of a good starting point
Predictive HEXBS • Consider the upper and the left neighboring blocks • Finding a good starting point using the neighboring motion vectors • Normally finds better motion vectors than the original HEXBS scheme
Fast Hexagonal Inner Search • Not a full inner search , only check a portion of 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
6-Side-Based Fast Inner Search • 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 • 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
Enhanced HEXBS Algorithm • HEXBS incorporate the 6-side-based fast inner search scheme • Moreover , incorporate the Predictive HEXBS • The reduction of number of search points for the enhanced HEXBS algorithm : (1) The prediction for a good starting point using the predictive HEXBS, (2) The fast inner search.
TABLE III , where Ni is the number of search points used in the Method i ,where MSEi is the distortions for Methods i
Conclusion • Enhanced HEXBS speeds up the motion estimation and decreases distortions • Only part of the inner points will be evaluated • Enhanced HEXBS algorithm outperforms the original HEXBS