An Adaptive Mode Decision Algorithm Based on Video Texture Characteristics for HEVC Intra Prediction

Xingang Liu, Yinbo Liu, Peicheng Wang, Chin Feng Lai, Han Chieh Chao

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)


The latest High Efficiency Video Coding (HEVC) standard could achieve the highest coding efficiency compared with the existing video coding standards. To improve the coding efficiency of the intra frame, a quad-Tree-based variable block size coding structure that is flexible to adapt to various texture characteristics of images and up to 35 intra-prediction modes for each prediction unit (PU) is adopted in HEVC. However, the computational complexity is increased dramatically because all the possible combinations of the mode candidates are calculated in order to find the optimal rate distortion cost using the Lagrange multiplier. To alleviate the encoder computational load, this paper proposes an adaptive mode decision algorithm based on texture complexity and direction for HEVC intra prediction. First, an adaptive coding unit selection algorithm according to each depth levels' texture complexity is presented to filter out unnecessary coding block. Then, the original redundant mode candidates for each PU are reduced according to its texture direction. The simulation results show that the proposed algorithm could reduce around 56% encoding time on average while maintaining the encoding performance efficiently with only a 1.0% increase in BD-rate compared with the test model HM16 of HEVC.

Original languageEnglish
Article number7457295
Pages (from-to)1737-1748
Number of pages12
JournalIEEE Transactions on Circuits and Systems for Video Technology
Issue number8
Publication statusPublished - 2017 Aug

All Science Journal Classification (ASJC) codes

  • Media Technology
  • Electrical and Electronic Engineering

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