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An energy-aware system-on-chip architecture for intra prediction in HEVC standard

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 9 No. 6 (2019)

DOI
10.11591/ijece.v9i6.pp5084-5094
ISSN
2088-8708, 2088-8708
Published
2019-12-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

High resolution 4K and 8K are becoming the more used in video applications. Those resolutions are well supported in the new HEVC standard. Thus, embedded solutions such as development of dedicated ystems-On-Chips (SOC) to accelerate video processing on one chip instead of only software solutions are commendable. This paper proposes a novel parallel and high efficient hardware accelerator for the intra prediction block. This accelerator achieves a high-speed treatment due to pipelined processing units and parallel shaped architecture. The complexity of memory access is also reduced thanks to the proposed design with less increased power consumption. The implementation was performed on the 7 Series FPGA 28 nm technology resources on Zynq-7000 and results show, that the proposed architecture takes 16520 LUTs and can reach 143.65 MHz as a maximum frequency and it is able to support the throughput of 3840×2160 sequence at 90 frames per second.

Collaboration network of the authors

8 authors · 17 co-authorship links · 6 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Sidi Mohamed Ben Abdellah University
  • University of Sfax
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Anass MansouriSidi Mohamed Ben Abdellah University3
Nejmeddine BahriUniversity of Sfax2
Nouri MasmoudUniversity of Sfax2
Mouhcine RaziSidi Mohamed Ben Abdellah University1
Mhammed BenhayounSidi Mohamed Ben Abdellah University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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