Mode-dependent pixel-based weighted intraprediction for HEVC scalable extension
Author(s) -
Tang Nguyen,
Chun-Chi Chen
Publication year - 2014
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.2064639
Subject(s) - weighting , scalability , pixel , computer science , algorithm , extension (predicate logic) , coding (social sciences) , mode (computer interface) , block (permutation group theory) , layer (electronics) , artificial intelligence , pattern recognition (psychology) , data mining , mathematics , statistics , chemistry , geometry , operating system , medicine , radiology , organic chemistry , database , programming language
The current draft scalable extension to HEVC offers two approaches, RefIdx and TextureRL, for performing inter-layer prediction. In the framework of TextureRL, this paper presents a mode-dependent pixel-based weighted intra prediction scheme for coding the enhancement layer (EL). The scheme first decomposes the EL intra prediction and the collocated base layer reconstructed block into their respective DC and AC components and then computes a weighted sum of both to form a better prediction signal using a pixel-based weighting scheme. The weighting factors to associate with different components are obtained by a least-squares fit to the training data. It was observed that they depend strongly on the EL's intra prediction mode and prediction block size, but are less dependent on QP settings. The experimental results show an average BD-rate savings of 1.0% for the AI-2x configuration and 0.5% for AI-1.5x over the SHM-1.0 anchor.
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