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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 a Petr HOLUB. Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures. In Storer, James A. and Marcellin, Michael W. \textit{Data Compression Conference (DCC), 2011}. Washington, DC, USA: IEEE Computer Society, 2011, s.~423-432. ISBN~978-0-7695-4352-9. Dostupné z: https://dx.doi.org/10.1109/DCC.2011.49.
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