A Complexity Reduction Method for Intra Prediction Method in HEVC Standard

Mirian, Zahra; Ramezanpour, Mohammadreza

doi:10.30486/mjee.2022.696502

Document Type : Reseach Article

Authors

¹ Islamic Azad University Mobarakeh BranchDepartment of Computer Engineering, Mobarakeh Branch, Islamic Azad University, Isfahan, Iran

² Islamic Azad University Mobarakeh BrDepartment of Computer Engineering, Mobarakeh Branch, Islamic Azad University, Isfahan, Irananch

https://doi.org/10.30486/mjee.2022.696502

Abstract

High Efficiency Video Coding (HEVC) is considered the last standard for video compression with about 50% additional compression compared to the previous standard i.e. H264/AVC, while maintaining image quality. The significant increase in performance of this standard has been achieved with high computational complexity. In this standard, the intra prediction unit is one of the parts that although it greatly improves performance, it significantly increases its computational complexity due to the increase in the number of prediction modes. In this paper, a method has been proposed to reduce the number of intra prediction modes in HEVC by which the computational complexity of compression at this stage can be reduced as much as possible. The proposed method determines the predominant mode of 4 × 4 blocks, and the details in each larger block, and accordingly, by applying the appropriate filters and selecting the most likely mode, the number of candidate modes to select the best mode is reduced. The simulation results showed that on average the proposed method can reduce the compression time by 45% while increasing the bit rate by 0.69%.

Keywords

References

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Majlesi Journal of Electrical Engineering

A Complexity Reduction Method for Intra Prediction Method in HEVC Standard

References

References

Volume 16, Issue 3 - Serial Number 3
September 2022
Pages 19-25

A Complexity Reduction Method for Intra Prediction Method in HEVC Standard

References

References

Volume 16, Issue 3 - Serial Number 3September 2022Pages 19-25

Volume 16, Issue 3 - Serial Number 3
September 2022
Pages 19-25