On lossless intra coding in HEVC with 3-tap filters

作者:

Highlights:

• This paper presents a pixel-by-pixel spatial prediction method for lossless intra coding within High Efficiency Video Coding (HEVC).

• Previous pixel-by-pixel spatial prediction methods are based on the angular projection idea borrowed from block-based intra prediction in lossy coding.

• This paper explores a pixel-by-pixel prediction method which uses three neighboring pixels for prediction according to a two-dimensional correlation model.

• This paper develops a unified prediction algorithm applied in all intra modes with optimized prediction weights and neighbors.

• The prediction weights for each intra mode are determined from a two-stage offline optimization algorithm.

• Experimental results show that the method can achieve an average 11.34% bitrate reduction over the default lossless intra coding in HEVC.

• The method decreases average decoding time by 12.7% while increasing average encoding time by 9.7%.

摘要

Highlights•This paper presents a pixel-by-pixel spatial prediction method for lossless intra coding within High Efficiency Video Coding (HEVC).•Previous pixel-by-pixel spatial prediction methods are based on the angular projection idea borrowed from block-based intra prediction in lossy coding.•This paper explores a pixel-by-pixel prediction method which uses three neighboring pixels for prediction according to a two-dimensional correlation model.•This paper develops a unified prediction algorithm applied in all intra modes with optimized prediction weights and neighbors.•The prediction weights for each intra mode are determined from a two-stage offline optimization algorithm.•Experimental results show that the method can achieve an average 11.34% bitrate reduction over the default lossless intra coding in HEVC.•The method decreases average decoding time by 12.7% while increasing average encoding time by 9.7%.

论文关键词:Image coding,Video coding,Lossless coding,Intra prediction

论文评审过程:Received 6 January 2016, Revised 1 June 2016, Accepted 13 June 2016, Available online 1 July 2016, Version of Record 14 July 2016.

论文官网地址:https://doi.org/10.1016/j.image.2016.06.006