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@inproceedings{916772,
author = {Matela, Jiří and Rusňák, Vít and Holub, Petr},
address = {Washington, DC, USA},
booktitle = {Data Compression Conference (DCC), 2011},
doi = {http://dx.doi.org/10.1109/DCC.2011.49},
editor = {Storer, James A. and Marcellin, Michael W.},
keywords = {JPEG2000; EBCOT; Parallel; Contex Modeling; GPU; GPGPU; CUDA},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Washington, DC, USA},
isbn = {978-0-7695-4352-9},
pages = {423-432},
publisher = {IEEE Computer Society},
title = {Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures},
year = {2011}
}
TY - JOUR
ID - 916772
AU - Matela, Jiří - Rusňák, Vít - Holub, Petr
PY - 2011
TI - Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures
PB - IEEE Computer Society
CY - Washington, DC, USA
SN - 9780769543529
KW - JPEG2000
KW - EBCOT
KW - Parallel
KW - Contex Modeling
KW - GPU
KW - GPGPU
KW - CUDA
N2 - Embedded Block Coding with Optimal Truncation (EBCOT) is the fundamental and computationally very demanding part of the compression process of JPEG2000 image compression standard. In this paper, we present a reformulation of the context modeling of EBCOT that allows full parallelization for massively parallel architectures such as GPUs with their single instruction multiple threads architecture. We prove that the reformulation is equivalent to the EBCOT specification in JPEG2000 standard. Behavior of the reformulated algorithm is demonstrated using NVIDIA CUDA platform and compared to other state-of-the-art implementations.
ER -
MATELA, Jiří, Vít RUSŇÁK and Petr HOLUB. Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures. Online. In Storer, James A. and Marcellin, Michael W. \textit{Data Compression Conference (DCC), 2011}. Washington, DC, USA: IEEE Computer Society, 2011. p.~423-432. ISBN~978-0-7695-4352-9. Available from: https://dx.doi.org/10.1109/DCC.2011.49. [citováno 2024-04-24]
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