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KSVM-Based Fast Intra Mode Prediction in HEVC Using Statistical Features and Sparse Autoencoder | IEEE Journals & Magazine | IEEE Xplore

KSVM-Based Fast Intra Mode Prediction in HEVC Using Statistical Features and Sparse Autoencoder


Optimal mode prediction using the proposed SVM method.

Abstract:

High Efficiency Video Coding (HEVC) is designed to deliver a video communication with better quality at reduced bit rate. For intra coding, HEVC employs an effective hier...Show More

Abstract:

High Efficiency Video Coding (HEVC) is designed to deliver a video communication with better quality at reduced bit rate. For intra coding, HEVC employs an effective hierarchical quad tree partitioning and an exhaustive optimal mode search which increases the time complexity. Aiming this issue, we propose a Support Vector Machine (SVM)-based method to effectively predict the intra mode. Compared to the standard HEVC encoder HM-15.0, the proposed method could reduce 57.6% of encoding time at a bit-rate penalty of 3.3% at an average PSNR decline of only around 0.09 dB.
Optimal mode prediction using the proposed SVM method.
Published in: IEEE Access ( Volume: 12)
Page(s): 48846 - 48852
Date of Publication: 27 March 2024
Electronic ISSN: 2169-3536

Funding Agency:


References

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