@inproceedings{19242c71085c4e55976c5e1abf8c793b,
title = "A High throughput and energy-efficient retina-inspired tone mapping processor",
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.",
keywords = "Energy Efficient, Retina Inspired, Tone Mapping Processor",
author = "Lili Liu and Xiaoqiang Xiang and Yuxiang Xie and Yongjie Li and Bo Yan and Jun Zhou",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 27th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019 ; Conference date: 28-04-2019 Through 01-05-2019",
year = "2019",
month = apr,
doi = "10.1109/FCCM.2019.00062",
language = "English",
series = "Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "321",
booktitle = "Proceedings - 27th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2019",
address = "United States",
}