Efficient Intra and Most Probable Mode (MPM) Selection Based on Statistical Texture Features


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High Efficiency video coding (HEVC) Encoder could give higher compression efficiency by offering 35 intra modes. However, this increases the complexity of the encoder due to more modes participate in the decision process. Therefore, it is necessary to build a fast and efficient intra prediction algorithm that is practical for real time application. Statistical properties of reference samples and the current intra block can be investigated to find out which modes will be efficient for the current block. Therefore, an adaptive and efficient modes selection model is presented in this paper. Firstly, intra modes are efficiently short listed by calculating the Euclidean distance between the statistical features of the reference samples and the current block. Secondly, an efficient MPM selection method is proposed that selects the modes for MPM by investigating the correlation between the neigh boring blocks and the current block. Experimental results demonstrate that average BD-Rate saving of the proposed approach is-0.11%, and BD-PSNR is improved by 0.0065%.
Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
Publication statusPublished - Oct 2015
Externally publishedYes


  • features
  • High Efficiency Video Coding (HEVC)
  • Most Probable Mode
  • MPM
  • Rate distortion optimization
  • RDOQ
  • RMD
  • Rough mode Decision


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