One-Pass Mode and Motion Decision for Multilayer Quality Scalable Video Coding

Meng Xu, Zhan Ma, Yao Wang

Research output: Contribution to journalArticle

Abstract

This paper presents a novel low-complexity motion estimation and mode decision algorithm for encoding multiple quality layers following the H.264/scalable video coding standard, considering both coarse grain scalability (CGS) and medium grain scalability (MGS). The proposed algorithm conducts motion estimation and mode decision only at the base layer (BL) and enforces the higher layers to inherit the motion and mode decisions of the BL. In order for the decision made at the BL to be nearly optimal for all layers, we use the highest layer reconstructed frame as the reference frame for motion estimation and set the Lagrangian multipliers according to the quantization parameter of the current and higher layers. We also propose a simple early skip/direct decision to further boost the encoding speed. Mode decision and motion estimation is conducted at a higher layer only if the layer below it uses the skip/direct mode for a block. Significant complexity reduction can be achieved because the mode and motion estimation is performed at most once for each macroblock. Because the mode and motion information only needs to be transmitted once, we also achieve a slightly better rate-distortion (R-D) performance for typical videos. Experiments have shown more than 2× (up to 5×) speedup for a three-layer encoder against the conventional R-D optimized reference software JSVM on both CIF and HD sequences, and for both CGS and MGS, with the tradeoff of the coding efficiency measured by the Bjontegaard delta rate.

Original languageEnglish (US)
Article number7172494
Pages (from-to)4250-4262
Number of pages13
JournalIEEE Transactions on Image Processing
Volume24
Issue number11
DOIs
StatePublished - Nov 1 2015

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Keywords

  • CGS
  • Fast motion and mode decsion
  • H.264/SVC
  • MGS

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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