Paper
16 April 2014 Mode-dependent pixel-based weighted intraprediction for HEVC scalable extension
Tang Kha Duy Nguyen, Chun-Chi Chen
Author Affiliations +
Proceedings Volume 9159, Sixth International Conference on Digital Image Processing (ICDIP 2014); 915925 (2014) https://doi.org/10.1117/12.2064639
Event: Sixth International Conference on Digital Image Processing, 2014, Athens, Greece
Abstract
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.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tang Kha Duy Nguyen and Chun-Chi Chen "Mode-dependent pixel-based weighted intraprediction for HEVC scalable extension", Proc. SPIE 9159, Sixth International Conference on Digital Image Processing (ICDIP 2014), 915925 (16 April 2014); https://doi.org/10.1117/12.2064639
Lens.org Logo
CITATIONS
Cited by 1 patent.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Electroluminescence

Artificial intelligence

Evolutionary algorithms

Detection and tracking algorithms

Mathematical modeling

Spatial resolution

Structural health monitoring

Back to Top