GPU-Oriented architecture for an end-to-end image/video codec based on JPEG2000

Carlos De Cea-Dominguez*, Juan C. Moure-Lopez, Joan Bartrina-Rapesta, Francesc Auli-Llinas

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

Abstract

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.

Original languageAmerican English
Article number9057501
Pages (from-to)68474-68487
Number of pages14
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 2020

Keywords

  • CUDA
  • GPU
  • high-throughput image coding
  • JPEG2000
  • Wavelet-based image coding

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