Motion vector memory reduction scheme for scalable motion estimation

Jinha Choi, Jaeseok Kim

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We propose a motion vector memory reduction scheme for the H.264 spatial scalable motion estimation. The spatial scalable prediction of H.264 scalable video coding requires a significant amount of motion vector bits from the previous layer motion prediction. This motion vector causes the Internal memory size to increase, which may result in increasing hardware cost and power consumption. To reduce the memory size of the motion vector, we propose a motion vector bit-compression scheme of the interlayer motion estimation. The proposed compression scheme uses the difference value of current motion vector and previous motion vector to get a probability for entropy coding. In addition, the proposed scheme modifies a variable length coding table of the H.264 system as a simple entropy coding table. The proposed scheme reduces the motion vector- storing bit by ∼66.5% with less changes in hardware size.

Original languageEnglish
Article number090502
JournalOptical Engineering
Volume48
Issue number9
DOIs
Publication statusPublished - 2009 Sep 23

Fingerprint

Motion estimation
Data storage equipment
coding
Entropy
Scalable video coding
hardware
entropy
Computer hardware
Electric power utilization
predictions
Hardware
interlayers
costs
Costs

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)

Cite this

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Motion vector memory reduction scheme for scalable motion estimation. / Choi, Jinha; Kim, Jaeseok.

In: Optical Engineering, Vol. 48, No. 9, 090502, 23.09.2009.

Research output: Contribution to journalArticle

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