A High Throughput JPEG2000 Entropy Decoding Unit Architecture

Liu, Kai; Belyaev, Evgeny; Li, Yunsong

doi:10.1007/s11265-018-1411-6

Cited by 2 publications

(1 citation statement)

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“…In medical and remote sensing applications, dedicated servers and workstations are employed to manage and store the large quantity of images that are produced daily [10], [11]. This has motivated many works in the literature that propose hardware architectures to accelerate particular stages of the JPEG2000 coding pipeline [12]- [22].…”

Section: Introductionmentioning

confidence: 99%

GPU-Oriented Architecture for an End-to-End Image/Video Codec Based on JPEG2000

et al. 2020

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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. INDEX TERMS Wavelet-based image coding, high-throughput image coding, JPEG2000, GPU, CUDA.

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Section: Introductionmentioning

confidence: 99%