Fast transrating for high efficiency video coding based on machine learning
Luong Pham Van, Jan De Cock, Glenn Van Wallendael, Sebastiaan Van Leuven, Rafael Rodríguez‐Sánchez, José Luis Martínez, Peter Lambert, Rik Van de Walle · 2013
To incorporate the newly developed High Efficiency Video Coding (HEVC) standard in real-life network applications, efficient transrating algorithms are required. We propose a fast transrating scheme, based on the early prediction of the partition split-flags in P pictures. Using machine learning techniques, the correlation between co-located partitions at different quantizations is investigated. This results in a model which predicts the split-flag and gives the associated prediction accuracy so that the splitting process in the transcoder is optimized. At each partition depth, the model indicates whether the full rate-distortion cost evaluations should be performed at the current depth, or if the partition can be split immediately. Experimental results show that the proposed transcoder reduces the complexity of the transrating process by 76.04%, while maintaining the coding efficiency of a cascaded decoder-encoder.