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Conference object . 2009 . Peer-reviewed
https://doi.org/10.1109/dcc.20...
Article . 2009 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2023
Data sources: DBLP
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Fast Intra Prediction in the Transform Domain

Authors: Chanyul Kim; Noel E. O'Connor; Yunje Oh;

Fast Intra Prediction in the Transform Domain

Abstract

The paper reports a new fast intra prediction algorithms based on separating the transformed coefficients of neighboring blocks. The prediction blocks are obtained from the transformed and quantized neighboring blocks that generate minimum distortion for each DC and AC coefficients. To obtain fast coding with comparable coding efficiency compared to H.264/AVC, we present the Full Block Search Prediction (FBSP) and the Edge Based Distance Prediction (EBDP). These are immune to both the intra prediction error and the drift propagation; in addition, do not require a low pass filtering named extrapolation and mode decisions to obtain a prediction block. Experimental results show that the use of transform coefficients greatly enhances the efficiency of intra prediction whilst keeping complexity low compared to H.264/AVC.

Country
Ireland
Keywords

Video compression, Image processing, Digital video, Algorithms

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green