Publication Type : Journal Article
Publisher : Institute of Electrical and Electronics Engineers (IEEE)
Source : IEEE Access
Url : https://doi.org/10.1109/access.2024.3382570
Campus : Amritapuri
School : School of Computing
Year : 2024
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.
Cite this Research Publication : Preethi S. Nair, Madhu S. Nair, KSVM-Based Fast Intra Mode Prediction in HEVC Using Statistical Features and Sparse Autoencoder, IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), 2024, https://doi.org/10.1109/access.2024.3382570