Fast mode-decision for H.264/AVC based on inter-frame correlations

Hyunsuk Ko, Kiwon Yoo, Kwanghoon Sohn

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

The H.264/AVC standard yields higher coding efficiency rates than other video coding standards. This is because it uses the rate-distortion optimization (RDO) technique, which selects the optimal coding mode and a reference frame for each macroblock (MB). In order to achieve this, the encoder has to encode a given block by exhaustively using all kinds of combinations (including different intra and inter-prediction modes). As a result, the computational complexity of video coding in H.264/AVC is extremely high. In this paper, two fast intra-/inter-mode-decision algorithms are proposed to reduce the complexity of the encoder. Both of these algorithms are based on the inter-frame correlation among adjacent pictures. For the fast intra-mode-decision, we used the intra-mode of the most-correlated MB at the reference frame to encode the current MB and the stationary property of the current MB was used for the fast inter-mode-decision. The simulation results show that the proposed algorithms significantly reduced the computational complexity with a negligible loss of PSNR and a slight increase in bitrate.

Original languageEnglish
Pages (from-to)803-813
Number of pages11
JournalSignal Processing: Image Communication
Volume24
Issue number10
DOIs
Publication statusPublished - 2009 Nov

Bibliographical note

Funding Information:
We would like to thank LG Electronics for providing the images. This work was partially supported by the Korea Science and Engineering Foundation (KOSEF) through the Biometrics Engineering Research Center (BERC) at Yonsei University (No. R112002105070030(2009)) and was partially supported by the Ministry of Knowledge Economy (MKE), Korea, under the Information Technology Research Center (ITRC) support program supervised by the Institute for Information Technology Advancement [IITA; IITA-2009-(C1090-0902-0011)].

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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