戴荣时1,
俞峰1,
王天鹏1
1.东南大学电子科学与工程学院 南京 210096
2.光电控制技术重点实验室 洛阳 471009
基金项目:航空科学基金(20155169017)
详细信息
作者简介:汤勇明:男,1973年生,博士,研究员,主要研究方向为显示电子学、嵌入式系统应用、FPGA加速设计
戴荣时:男,1997年生,硕士生,主要研究方向为数字图像处理、FPGA加速设计
俞峰:男,1997年生,硕士生,主要研究方向为数字图像处理、FPGA编程开发
王天鹏:男,1995年生,硕士生,主要研究方向为电路与系统、FPGA加速设计
通讯作者:汤勇明 tym@seu.edu.cn
中图分类号:TN911.73计量
文章访问数:282
HTML全文浏览量:156
PDF下载量:52
被引次数:0
出版历程
收稿日期:2020-07-06
修回日期:2021-06-21
网络出版日期:2021-08-09
刊出日期:2021-09-16
Design of Adaptive Video Image Dehazing Algorithm and FPGA Accelerated Implementation
Yongming TANG1, 2,,,Rongshi DAI1,
Feng YU1,
Tianpeng WANG1
1. School of Electronic Science & Engineering, Southeast University, Nanjing 210096, China
2. Science and Technology on Electro-optic Control Laboratory, Luoyang 471009, China
Funds:Aeronautical Science Foundation of China (20155169017)
摘要
摘要:该文提出了一种自适应图像去雾算法,充分考虑不同复杂场景下的图像特征,建立了算法的自适应机制。该机制包含对图像是否有雾、是否为天空区域、滤波器尺寸等的自适应调整,解决了传统图像去雾算法在深度断层处可能产生的光晕效应等问题。该文同时对上述自适应图像去雾算法进行FPGA加速实现,实验结果表明,该文算法在XC7K325T型号FPGA视频处理平台上可以满足对1080P@60Hz视频去雾的实时性要求。对于大多数轻雾或浓雾场景,该文算法去雾后图像色彩自然无过饱和,全局对比度和饱和度提升比率均值为0.309和0.994,相比于本领域其他去雾算法优势明显。
关键词:视频图像去雾/
自适应机制/
实时性去雾/
FPGA实现
Abstract:This paper proposes an adaptive image dehazing algorithm, which fully considers the image features in different complex scenes and establishes an adaptive mechanism of the algorithm. The mechanism includes adaptive adjustments to whether the image is foggy, whether it is a sky area, or filter size, etc., which solves the bad effect that the traditional algorithm may cause when dehazing the depth mutation region. This article also implements FPGA acceleration for the adaptive image dehazing algorithm. Experimental results show that the algorithm can meet the real-time requirements of 1080P@60Hz video dehazing on XC7K325T FPGA video processing platform. For most light fog or heavy fog scenes, the image color of this algorithm is naturally free of oversaturation after dehazing. The average global contrast and saturation enhancement ratio are 0.309 and 0.994, which has obvious advantages compared with other dehazing algorithms in the field.
Key words:Video dehaze/
Adaptive mechanism/
Real-time dehaze/
Implementation on FPGA
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https://jeit.ac.cn/article/exportPdf?id=23768a09-7eda-40eb-82bb-598770b1a6a2