TY - JOUR
T1 - GPU-Oriented architecture for an end-to-end image/video codec based on JPEG2000
AU - De Cea-Dominguez, Carlos
AU - Moure-Lopez, Juan C.
AU - Bartrina-Rapesta, Joan
AU - Auli-Llinas, Francesc
PY - 2020
Y1 - 2020
N2 - Modern image and video compression standards employ computationally intensive algorithms that provide advanced features to the coding system. Current standards often need to be implemented in hardware or using expensive solutions to meet the real-time requirements of some environments. Contrarily to this trend, this paper proposes an end-to-end codec architecture running on inexpensive Graphics Processing Units (GPUs) that is based on, though not compatible with, the JPEG2000 international standard for image and video compression. When executed in a commodity Nvidia GPU, it achieves real time processing of 12K video. The proposed S/W architecture utilizes four CUDA kernels that minimize memory transfers, use registers instead of shared memory, and employ a double-buffer strategy to optimize the streaming of data. The analysis of throughput indicates that the proposed codec yields results at least 10 × superior on average to those achieved with JPEG2000 implementations devised for CPUs, and approximately 4 × superior to those achieved with hardwired solutions of the HEVC/H.265 video compression standard.
AB - Modern image and video compression standards employ computationally intensive algorithms that provide advanced features to the coding system. Current standards often need to be implemented in hardware or using expensive solutions to meet the real-time requirements of some environments. Contrarily to this trend, this paper proposes an end-to-end codec architecture running on inexpensive Graphics Processing Units (GPUs) that is based on, though not compatible with, the JPEG2000 international standard for image and video compression. When executed in a commodity Nvidia GPU, it achieves real time processing of 12K video. The proposed S/W architecture utilizes four CUDA kernels that minimize memory transfers, use registers instead of shared memory, and employ a double-buffer strategy to optimize the streaming of data. The analysis of throughput indicates that the proposed codec yields results at least 10 × superior on average to those achieved with JPEG2000 implementations devised for CPUs, and approximately 4 × superior to those achieved with hardwired solutions of the HEVC/H.265 video compression standard.
KW - CUDA
KW - GPU
KW - JPEG2000
KW - Wavelet-based image coding
KW - high-throughput image coding
UR - http://www.scopus.com/inward/record.url?scp=85084112927&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/ACCESS.2020.2985859
DO - https://doi.org/10.1109/ACCESS.2020.2985859
M3 - Artículo
AN - SCOPUS:85084112927
VL - 8
SP - 68474
EP - 68487
JO - IEEE Access
JF - IEEE Access
SN - 2169-3536
M1 - 9057501
ER -