Lossy strict multilevel successive elimination algorithm for fast motion estimation

Yang Song, Zhenyu Liu, Takeshi Ikenaga, Satoshi Goto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper present a simple and effective method to further reduce the search points in the multilevel successive elimination algorithm (MSEA). Because the sea values for most of the best matching search positions are much smaller than the current minimum SAD, we can simply increase the calculated sea value to increase the elimination ratio without much affecting the coding efficiency. Compared with the MSEA algorithm, experiments show that the proposed strict MSEA algorithm (SMSEA) can provides almost 6.5 times speedup with stable image quality, which is better than diamond search (DS). In practice, the proposed technique can also be used in the fine granularity SEA (FGSE) algorithm and the calculation process can be traced by analogy.

Original languageEnglish
Title of host publication2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06
Pages431-434
Number of pages4
DOIs
Publication statusPublished - 2007
Event2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06 - Yonago
Duration: 2006 Dec 122006 Dec 15

Other

Other2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06
CityYonago
Period06/12/1206/12/15

Fingerprint

Motion Estimation
Motion estimation
Elimination
Granularity
Strombus or kite or diamond
Image Quality
Image quality
Analogy
Diamonds
Speedup
Coding
Experiment
Experiments

ASJC Scopus subject areas

  • Computer Science Applications
  • Signal Processing
  • Software
  • Electrical and Electronic Engineering
  • Mathematics(all)

Cite this

Song, Y., Liu, Z., Ikenaga, T., & Goto, S. (2007). Lossy strict multilevel successive elimination algorithm for fast motion estimation. In 2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06 (pp. 431-434). [4212309] https://doi.org/10.1109/ISPACS.2006.364691

Lossy strict multilevel successive elimination algorithm for fast motion estimation. / Song, Yang; Liu, Zhenyu; Ikenaga, Takeshi; Goto, Satoshi.

2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06. 2007. p. 431-434 4212309.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Song, Y, Liu, Z, Ikenaga, T & Goto, S 2007, Lossy strict multilevel successive elimination algorithm for fast motion estimation. in 2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06., 4212309, pp. 431-434, 2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06, Yonago, 06/12/12. https://doi.org/10.1109/ISPACS.2006.364691
Song Y, Liu Z, Ikenaga T, Goto S. Lossy strict multilevel successive elimination algorithm for fast motion estimation. In 2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06. 2007. p. 431-434. 4212309 https://doi.org/10.1109/ISPACS.2006.364691
Song, Yang ; Liu, Zhenyu ; Ikenaga, Takeshi ; Goto, Satoshi. / Lossy strict multilevel successive elimination algorithm for fast motion estimation. 2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06. 2007. pp. 431-434
@inproceedings{5a8ab05558a94e18a67050dcfd56a423,
title = "Lossy strict multilevel successive elimination algorithm for fast motion estimation",
abstract = "This paper present a simple and effective method to further reduce the search points in the multilevel successive elimination algorithm (MSEA). Because the sea values for most of the best matching search positions are much smaller than the current minimum SAD, we can simply increase the calculated sea value to increase the elimination ratio without much affecting the coding efficiency. Compared with the MSEA algorithm, experiments show that the proposed strict MSEA algorithm (SMSEA) can provides almost 6.5 times speedup with stable image quality, which is better than diamond search (DS). In practice, the proposed technique can also be used in the fine granularity SEA (FGSE) algorithm and the calculation process can be traced by analogy.",
author = "Yang Song and Zhenyu Liu and Takeshi Ikenaga and Satoshi Goto",
year = "2007",
doi = "10.1109/ISPACS.2006.364691",
language = "English",
isbn = "0780397339",
pages = "431--434",
booktitle = "2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06",

}

TY - GEN

T1 - Lossy 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 present a simple and effective method to further reduce the search points in the multilevel successive elimination algorithm (MSEA). Because the sea values for most of the best matching search positions are much smaller than the current minimum SAD, we can simply increase the calculated sea value to increase the elimination ratio without much affecting the coding efficiency. Compared with the MSEA algorithm, experiments show that the proposed strict MSEA algorithm (SMSEA) can provides almost 6.5 times speedup with stable image quality, which is better than diamond search (DS). In practice, the proposed technique can also be used in the fine granularity SEA (FGSE) algorithm and the calculation process can be traced by analogy.

AB - This paper present a simple and effective method to further reduce the search points in the multilevel successive elimination algorithm (MSEA). Because the sea values for most of the best matching search positions are much smaller than the current minimum SAD, we can simply increase the calculated sea value to increase the elimination ratio without much affecting the coding efficiency. Compared with the MSEA algorithm, experiments show that the proposed strict MSEA algorithm (SMSEA) can provides almost 6.5 times speedup with stable image quality, which is better than diamond search (DS). In practice, the proposed technique can also be used in the fine granularity SEA (FGSE) algorithm and the calculation process can be traced by analogy.

UR - http://www.scopus.com/inward/record.url?scp=45249115329&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=45249115329&partnerID=8YFLogxK

U2 - 10.1109/ISPACS.2006.364691

DO - 10.1109/ISPACS.2006.364691

M3 - Conference contribution

AN - SCOPUS:45249115329

SN - 0780397339

SN - 9780780397330

SP - 431

EP - 434

BT - 2006 International Symposium on Intelligent Signal Processing and Communications, ISPACS'06

ER -