Lossy Strict Multilevel Successive Elimination Algorithm for Fast Motion Estimation
Summary :
This paper presents a simple and effective method to further reduce the search points in multilevel successive elimination algorithm (MSEA). Because the calculated sea values of those best matching search points are much smaller than the current minimum SAD, we can simply increase the calculated sea values to increase the elimination ratio without much affecting the coding quality. Compared with the original MSEA algorithm, the proposed strict MSEA algorithm (SMSEA) can provide average 6.52 times speedup. Compared with other lossy fast ME algorithms such as TSS and DS, the proposed SMSEA can maintain more stable image quality. In practice, the proposed technique can also be used in the fine granularity SEA (FGSEA) algorithm and the calculation process is almost the same.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E90-A No.4 pp.764-770
- Publication Date
- 2007/04/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e90-a.4.764
- Type of Manuscript
- Special Section PAPER (Special Section on Selected Papers from the 19th Workshop on Circuits and Systems in Karuizawa)
- Category
Authors
Keyword
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Yang SONG, Zhenyu LIU, Takeshi IKENAGA, Satoshi GOTO, "Lossy Strict Multilevel Successive Elimination Algorithm for Fast Motion Estimation" in IEICE TRANSACTIONS on Fundamentals,
vol. E90-A, no. 4, pp. 764-770, April 2007, doi: 10.1093/ietfec/e90-a.4.764.
Abstract: This paper presents a simple and effective method to further reduce the search points in multilevel successive elimination algorithm (MSEA). Because the calculated sea values of those best matching search points are much smaller than the current minimum SAD, we can simply increase the calculated sea values to increase the elimination ratio without much affecting the coding quality. Compared with the original MSEA algorithm, the proposed strict MSEA algorithm (SMSEA) can provide average 6.52 times speedup. Compared with other lossy fast ME algorithms such as TSS and DS, the proposed SMSEA can maintain more stable image quality. In practice, the proposed technique can also be used in the fine granularity SEA (FGSEA) algorithm and the calculation process is almost the same.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e90-a.4.764/_p
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@ARTICLE{e90-a_4_764,
author={Yang SONG, Zhenyu LIU, Takeshi IKENAGA, Satoshi GOTO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Lossy Strict Multilevel Successive Elimination Algorithm for Fast Motion Estimation},
year={2007},
volume={E90-A},
number={4},
pages={764-770},
abstract={This paper presents a simple and effective method to further reduce the search points in multilevel successive elimination algorithm (MSEA). Because the calculated sea values of those best matching search points are much smaller than the current minimum SAD, we can simply increase the calculated sea values to increase the elimination ratio without much affecting the coding quality. Compared with the original MSEA algorithm, the proposed strict MSEA algorithm (SMSEA) can provide average 6.52 times speedup. Compared with other lossy fast ME algorithms such as TSS and DS, the proposed SMSEA can maintain more stable image quality. In practice, the proposed technique can also be used in the fine granularity SEA (FGSEA) algorithm and the calculation process is almost the same.},
keywords={},
doi={10.1093/ietfec/e90-a.4.764},
ISSN={1745-1337},
month={April},}
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TY - JOUR
TI - Lossy Strict Multilevel Successive Elimination Algorithm for Fast Motion Estimation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 764
EP - 770
AU - Yang SONG
AU - Zhenyu LIU
AU - Takeshi IKENAGA
AU - Satoshi GOTO
PY - 2007
DO - 10.1093/ietfec/e90-a.4.764
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E90-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2007
AB - This paper presents a simple and effective method to further reduce the search points in multilevel successive elimination algorithm (MSEA). Because the calculated sea values of those best matching search points are much smaller than the current minimum SAD, we can simply increase the calculated sea values to increase the elimination ratio without much affecting the coding quality. Compared with the original MSEA algorithm, the proposed strict MSEA algorithm (SMSEA) can provide average 6.52 times speedup. Compared with other lossy fast ME algorithms such as TSS and DS, the proposed SMSEA can maintain more stable image quality. In practice, the proposed technique can also be used in the fine granularity SEA (FGSEA) algorithm and the calculation process is almost the same.
ER -
English
