Hardware Development of Skylight Estimation Processing in Haze Removing Using High-level Synthesis

Daiki Shirai, A. Yamawaki
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Abstract

When monitoring infrastructure by using a drone, the real time advanced image processing on the drone can realize self-flying inspection. This result can reduce the burden of off-line processing to image data captured by the drone and realize quicker and more efficient infra monitoring method. In battery-powered embedded devices such as drones, hardware implementation is effective for realizing lowpower and high-performance image processing. In addition, the high-level synthesis automatically converting the software to the hardware module can handle different kinds of drones and image processing algorithms quickly and flexibly. Considering the aerial image of the drone, it is important to remove haze from the captured image from the viewpoint of noise removal for subsequent advanced image processing. In this paper, we propose a software description method for high-level synthesis in considering of hardware implementation of skylight estimation processing in haze removal processing by Kaiming He et al . In addition, we evaluate the performance of hardware, and show the effect of the proposed method.
基于高级综合的去雾天窗估计处理硬件开发
利用无人机对基础设施进行监控时,无人机上的实时高级图像处理可以实现自飞巡检。该结果可以减轻无人机捕获的图像数据的离线处理负担,实现更快、更高效的基础设施监测方法。在无人机等电池供电的嵌入式设备中,硬件实现是实现低功耗和高性能图像处理的有效途径。此外,高级合成自动将软件转换为硬件模块,可以快速灵活地处理不同类型的无人机和图像处理算法。考虑到无人机的航拍图像,从去噪的角度去除捕获图像中的雾霾对于后续的高级图像处理非常重要。本文考虑到何开明等人在雾霾去除处理中天窗估计处理的硬件实现,提出了一种高级综合的软件描述方法。此外,我们还对硬件性能进行了评估,并展示了所提出方法的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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