1 research outputs found
On Intra Prediction for Screen Content Video Coding
Screen content coding (SCC) is becoming increasingly important in various
applications, such as desktop sharing, video conferencing, and remote
education. When compared to natural camera- captured content, screen content
has different characteristics, in particular sharper 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 intra prediction to preserve the sharp
edges in screen content video. We present three different variants of the
proposed nearest neighbor prediction algorithm: two implicit methods where both
the encoder, and the decoder derive whether to perform nearest neighbor
prediction or not based on either (a) the sum of the absolute difference, or
(b) the difference between the boundary pixels from which prediction is
performed; and another variant where Rate-Distortion-Optimization (RDO) search
is performed at the encoder to decide whether or not to use the nearest
neighbor interpolation, and explicitly signaled to the decoder. We also discuss
the various underlying trade-offs in terms of the complexity of the three
variants. All the three proposed variants provide significant gains over HEVC,
and simulation results show that average gains of 3.3% BD-bitrate in
Intra-frame coding are achieved by the RDO variant for screen content video. To
the best of our knowledge, this is the first paper that 1) points out current
HEVC intra prediction scheme with bilinear interpolation does not work
efficiently for screen content video and 2) uses different filters adaptively
in the HEVC intra prediction interpolation