A High throughput and energy-efficient retina-inspired tone mapping processor

Lili Liu, Xiaoqiang Xiang, Yuxiang Xie, Yongjie Li, Bo Yan, Jun Zhou*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

This paper presents a high throughput and energy-efficient retina inspired tone mapping processor. Several hardware design techniques have been proposed to achieve high throughput and high energy efficiency, including data partition based parallel processing with S-shape sliding, adjacent frame feature sharing, multi-layer convolution pipelining and convolution filter compression with zero skipping convolution. The proposed processor has been implemented on a Xilinx's Virtex7 FPGA for demonstration. It is able to achieve a throughput of 189 frames per second for 1024∗768 RGB images with 819 mW. Compared with several state-of-The-Art tone mapping processors, the proposed processor achieves higher throughput and energy efficiency. It is suitable for high-speed and energy-constrained video enhancement applications such as autonomous vehicle and drone monitoring.

Original languageEnglish
Title of host publicationProceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages321
Number of pages1
ISBN (Electronic)9781728111315
DOIs
Publication statusPublished - Apr 2019
Externally publishedYes
Event27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019 - San Diego, United States
Duration: 28 Apr 20191 May 2019

Publication series

NameProceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019

Conference

Conference27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019
Country/TerritoryUnited States
CitySan Diego
Period28/04/191/05/19

Keywords

  • Energy Efficient
  • Retina Inspired
  • Tone Mapping Processor

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