Efficiency-complexity curve based method for evaluating adaptive search range algorithms in motion estimation

Zhenxing Chen*, Takeshi Ikenaga, Satoshi Goto

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

The well known Rate-Distortion (RD) curve and the average Peak Signal to Noise Ratio (PSNR) difference between two RD curves (APSNR) are frequently and widely used for evaluating how well a fast motion estimation (ME) algorithm performs in encoding efficiency. Besides this one for encoding efficiency, there usually exists another parameter, such as ME executing time or average search point number for processing one macroblock (ASP/MB), to evaluate the complexity of this fast ME algorithm. In the other hand, adaptive search range (ASR) ME algorithms are proved to be more fundamental, regular and controllable than normal fixed search pattern (FSP) ME algorithms. Thus for especially evaluating ASR ME algorithms, an Efficiency-Complexity (EC) curve based method is proposed and discussed in this paper.

Original languageEnglish
Title of host publicationProceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Pages525-528
Number of pages4
DOIs
Publication statusPublished - 2008 Sept 22
Event1st International Congress on Image and Signal Processing, CISP 2008 - Sanya, Hainan, China
Duration: 2008 May 272008 May 30

Publication series

NameProceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Volume1

Conference

Conference1st International Congress on Image and Signal Processing, CISP 2008
Country/TerritoryChina
CitySanya, Hainan
Period08/5/2708/5/30

Keywords

  • ASP/MB
  • ASR
  • EC
  • Evaluating
  • ΔPSNR

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing

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