Low-light image enhancement based on FPGA

Xiaohong Peng, Xuefeng Li, Shuqin Geng, Jie Wang, Fengjun Nie
{"title":"Low-light image enhancement based on FPGA","authors":"Xiaohong Peng, Xuefeng Li, Shuqin Geng, Jie Wang, Fengjun Nie","doi":"10.1109/asid52932.2021.9651721","DOIUrl":null,"url":null,"abstract":"This paper studies FPGA image processing, and proposes two methods to improve FPGA image processing acceleration, data reorganization and multi-processing modules. Both methods use ARM as the data control module. Data reorganization improves the transmission efficiency of the AXI bus by merging data, and the multiprocessing module improves the parallelism of the processing system by adding processing modules. Finally, these two methods are used to realize the low- light image enhancement algorithm combining wavelet transform and Retinex algorithm, and compared with the processing effect on matlab, and good results are obtained.","PeriodicalId":150884,"journal":{"name":"2021 IEEE 15th International Conference on Anti-counterfeiting, Security, and Identification (ASID)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 15th International Conference on Anti-counterfeiting, Security, and Identification (ASID)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/asid52932.2021.9651721","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This paper studies FPGA image processing, and proposes two methods to improve FPGA image processing acceleration, data reorganization and multi-processing modules. Both methods use ARM as the data control module. Data reorganization improves the transmission efficiency of the AXI bus by merging data, and the multiprocessing module improves the parallelism of the processing system by adding processing modules. Finally, these two methods are used to realize the low- light image enhancement algorithm combining wavelet transform and Retinex algorithm, and compared with the processing effect on matlab, and good results are obtained.
基于FPGA的微光图像增强
本文对FPGA图像处理进行了研究,提出了两种改进FPGA图像处理加速的方法:数据重组和多处理模块。两种方法都使用ARM作为数据控制模块。数据重组通过合并数据提高了AXI总线的传输效率,多处理模块通过增加处理模块提高了处理系统的并行性。最后,利用这两种方法实现了结合小波变换和Retinex算法的弱光图像增强算法,并在matlab上与处理效果进行了比较,取得了较好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信