Title | ||
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Lossless image and video coding based on H.264/AVC intra predictions with simplified interpolations |
Abstract | ||
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The lossy video coding is a key technology to compress the video to become very low bit rate data and H.264/AVC standard performs very well in lossy coding. However, the lossless image and video coding still plays an important role, especially in medical applications. Hence, the lossless coding in use of H.264/AVC gains a lot of attentions. In this paper, we introduce simplified interpolations to replace the sample-by-sample DPCM concept, which uses the nearer pixel as the prediction for certain modes to achieve better coding efficiency. The proposed predictions are applied to all intra prediction modes suggested in H.264/AVC. Moreover, the luma/chroma dc blocks reduction can also reduce the syntax elements for entropy coding. With these proposed algorithms, the compression performance of the H.264/AVC lossless intra coding is greatly improved. |
Year | DOI | Venue |
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2009 | 10.1109/ICIP.2009.5413839 | ICIP |
Keywords | Field | DocType |
h.264/avc,coding efficiency,lossless image,lossless coding,lossless image coding,interpolations,interpolation,h.264/avc lossless intra coding,sample-by-sample dpcm concept,video compression,lossless video coding,data compression,intra prediction mode,intra coding,avc intra prediction,video coding,avc gain,avc standard,lossless,prediction theory,lossy coding,luma/chroma dc blocks reduction,entropy codes,entropy coding,lossy video coding,prediction algorithms,encoding,pixel | Computer vision,Tunstall coding,Entropy encoding,Coding tree unit,Lossy compression,Context-adaptive variable-length coding,Computer science,Artificial intelligence,Data compression,Scalable Video Coding,Context-adaptive binary arithmetic coding | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4244-5655-0 | 978-1-4244-5655-0 | 6 |
PageRank | References | Authors |
0.87 | 2 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Shih-tse Wei | 1 | 21 | 3.13 |
Shang-Ru Shen | 2 | 6 | 0.87 |
Bin-da Liu | 3 | 563 | 66.56 |
Jar-Ferr Yang | 4 | 1115 | 142.85 |