Nearest-neighbor intra prediction for screen content video coding

Abstract

Screen content video coding is becoming increasingly important in various applications, such as desktop sharing, video conferencing, and remote education. In general, compared to natural camera-captured content, screen content has different characteristics, such as sharp edges. In this paper, we propose a novel intra prediction scheme for screen content video. In the proposed scheme, bilinear interpolation in angular intra prediction in HEVC is selectively replaced by nearest-neighbor (NN) interpolation to preserve the sharp edges in screen content video. We present two different variants of NN interpolation. In the first implicit pixel-based method, both the encoder, and the decoder determine whether to perform NN interpolation based on the prediction pixels. The second method comprises of the encoder performing a Rate-Distortion search at a block-level, and explicitly signaling a flag to the decoder to indicate when to use the NN interpolation. Both the proposed variants provide significant gains over HEVC, and simulation results show that average gains of 3.3% BD-bitrate are achieved for screen content video. The HEVC proposal of this method was accepted in the core experiments, and would be a technology under consideration in the ongoing Screen Content Coding extension of HEVC scheduled to begin in March 2014.