Enhanced strict multilevel successive elimination algorithm for fast motion estimation

Yang Song; Zhenyu Liu; Takeshi Ikenaga; Satoshi Goto

doi:10.1109/iscas.2007.378546

Enhanced strict multilevel successive elimination algorithm for fast motion estimation

Yang Song^*, Zhenyu Liu, Takeshi Ikenaga, Satoshi Goto

^*Corresponding author for this work

Graduate School of Information, Production and Systems

Research output: Contribution to journal › Conference article › peer-review

4 Citations (Scopus)

Abstract

This paper presents an enhanced strict multilevel successive elimination algorithm (EMSEA) for fast block-matching motion estimation, which is based on the previous strict multilevel successive elimination algorithm (SMSEA) [8]. Different to the SMSEA algorithm with fixed parameters, in EMSEA algorithm, the whole search area is divided into two regions and each region has its own parameters. Therefore, the computation complexity of SMSEA algorithm can be further decreased. Experiments show that the proposed EMSEA algorithm can reduce 16.2% of the SMSEA computation and maintain almost the same image quality, which is better than the TSS and DS algorithms.

Original language	English
Article number	4253474
Pages (from-to)	3659-3662
Number of pages	4
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
DOIs	https://doi.org/10.1109/iscas.2007.378546
Publication status	Published - 2007
Event	2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007 - New Orleans, LA, United States Duration: 2007 May 27 → 2007 May 30

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/iscas.2007.378546

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title = "Enhanced strict multilevel successive elimination algorithm for fast motion estimation",

abstract = "This paper presents an enhanced strict multilevel successive elimination algorithm (EMSEA) for fast block-matching motion estimation, which is based on the previous strict multilevel successive elimination algorithm (SMSEA) [8]. Different to the SMSEA algorithm with fixed parameters, in EMSEA algorithm, the whole search area is divided into two regions and each region has its own parameters. Therefore, the computation complexity of SMSEA algorithm can be further decreased. Experiments show that the proposed EMSEA algorithm can reduce 16.2% of the SMSEA computation and maintain almost the same image quality, which is better than the TSS and DS algorithms.",

author = "Yang Song and Zhenyu Liu and Takeshi Ikenaga and Satoshi Goto",

year = "2007",

doi = "10.1109/iscas.2007.378546",

language = "English",

pages = "3659--3662",

journal = "Proceedings - IEEE International Symposium on Circuits and Systems",

issn = "0271-4310",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007 ; Conference date: 27-05-2007 Through 30-05-2007",

}

TY - JOUR

T1 - Enhanced strict multilevel successive elimination algorithm for fast motion estimation

AU - Song, Yang

AU - Liu, Zhenyu

AU - Ikenaga, Takeshi

AU - Goto, Satoshi

PY - 2007

Y1 - 2007

N2 - This paper presents an enhanced strict multilevel successive elimination algorithm (EMSEA) for fast block-matching motion estimation, which is based on the previous strict multilevel successive elimination algorithm (SMSEA) [8]. Different to the SMSEA algorithm with fixed parameters, in EMSEA algorithm, the whole search area is divided into two regions and each region has its own parameters. Therefore, the computation complexity of SMSEA algorithm can be further decreased. Experiments show that the proposed EMSEA algorithm can reduce 16.2% of the SMSEA computation and maintain almost the same image quality, which is better than the TSS and DS algorithms.

AB - This paper presents an enhanced strict multilevel successive elimination algorithm (EMSEA) for fast block-matching motion estimation, which is based on the previous strict multilevel successive elimination algorithm (SMSEA) [8]. Different to the SMSEA algorithm with fixed parameters, in EMSEA algorithm, the whole search area is divided into two regions and each region has its own parameters. Therefore, the computation complexity of SMSEA algorithm can be further decreased. Experiments show that the proposed EMSEA algorithm can reduce 16.2% of the SMSEA computation and maintain almost the same image quality, which is better than the TSS and DS algorithms.

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DO - 10.1109/iscas.2007.378546

M3 - Conference article

AN - SCOPUS:34548819915

SN - 0271-4310

SP - 3659

EP - 3662

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

M1 - 4253474

T2 - 2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007

Y2 - 27 May 2007 through 30 May 2007

ER -

Enhanced strict multilevel successive elimination algorithm for fast motion estimation

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