Fast coding tree structure decision for HEVC based on classification trees

Abstract

The High Efficiency Video Coding (HEVC) standard provides improved compression rates in comparison to its predecessors at the cost of large increases in computational complexity. An important share of such increases is due to the introduction of flexible Coding Tree structures, which best configuration is decided through exhaustive tests in a rate-distortion optimization (RDO) scheme. In this work, an early termination method for the decision of such structures was designed using classification trees obtained through Data Mining techniques. The classification trees were trained using intermediate encoding results from a set of video sequences and implemented in the encoder to avoid the full RDO-based decision. An average reduction of 37 % in the HEVC encoder computational complexity was achieved when using the designed classification trees, with a negligible cost of only 0.28 % in terms of Bjontegaard Delta-rate increase.