Open AccessProbability Constrained Search Range Determination for Fast Motion Estimation
Author(s) -
Kang HyunSoo,
Lee SiWoong,
Hosseini Hamid Gholam
Publication year - 2012
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.12.0111.0200
Subject(s) - motion vector , motion estimation , computer science , range (aeronautics) , coding (social sciences) , search algorithm , pattern search , hyperparameter optimization , binary search algorithm , computational complexity theory , sampling (signal processing) , point (geometry) , grid , algorithm , artificial intelligence , computer vision , mathematics , support vector machine , statistics , engineering , image (mathematics) , geometry , filter (signal processing) , aerospace engineering
In this paper, we propose new adaptive search range motion estimation methods where the search ranges are constrained by the probabilities of motion vector differences and a search point sampling technique is applied to the constrained search ranges. Our new methods are based on our previous work, in which the search ranges were analytically determined by the probabilities. Since the proposed adaptive search range motion estimation methods effectively restrict the search ranges instead of search point sampling patterns, they provide a very flexible and hardware‐friendly approach in motion estimation. The proposed methods were evaluated and tested with JM16.2 of the H.264/AVC video coding standard. Experiment results exhibit that with negligible degradation in PSNR, the proposed methods considerably reduce the computational complexity in comparison with the conventional methods. In particular, the combined method provides performance similar to that of the hybrid unsymmetrical‐cross multi‐hexagon‐grid search method and outstanding merits in hardware implementation.