Quick defogging and cloud system realization for aerial image of guided filter

PAN Rong; SUN Wei; ZHAO Chun-yu

doi:10.3788/OPE.20172513.0191

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Quick defogging and cloud system realization for aerial image of guided filter

更新时间：2020-08-13

- Quick defogging and cloud system realization for aerial image of guided filter
- Optics and Precision Engineering Vol. 25, Issue 10s, Pages: 191-198(2017)
- 作者机构：
  
  西安电子科技大学空间科学与技术学院,陕西西安,710118
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20172513.0191
  CLC： TP391.41
- Received：01 June 2017，
  
  Revised：27 June 2017，
  
  Published：25 November 2017
- 稿件说明：
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潘蓉, 孙伟, 赵春宇. 导向滤波的航拍图像快速去雾方法及云系统实现[J]. 光学精密工程, 2017,25(10s): 191-198

PAN Rong, SUN Wei, ZHAO Chun-yu. Quick defogging and cloud system realization for aerial image of guided filter[J]. Editorial Office of Optics and Precision Engineering, 2017,25(10s): 191-198
潘蓉, 孙伟, 赵春宇. 导向滤波的航拍图像快速去雾方法及云系统实现[J]. 光学精密工程, 2017,25(10s): 191-198 DOI： 10.3788/OPE.20172513.0191.

PAN Rong, SUN Wei, ZHAO Chun-yu. Quick defogging and cloud system realization for aerial image of guided filter[J]. Editorial Office of Optics and Precision Engineering, 2017,25(10s): 191-198 DOI： 10.3788/OPE.20172513.0191.

摘要

提出一种基于导向滤波的航拍图像去雾方法，并实现了基于云计算的去雾系统用于视觉导航和侦察。首先通过暗影通道计算航拍图像的大气幕函数，利用导向滤波计算大气幕函数的边缘保持估计；然后计算原图像和大气幕函数的残差图像并提取其亮通道；最后根据光照反射模型获得场景的反射系数作为复原图像。该方法无需求取全局大气光，利用导向滤波算法可以获得更好的图像细节与整体可见度。与传统的无人机机载处理系统相比，借助云计算强大的分布式计算能力和海量存储能力使得该去雾系统更高效、快速，提高了无人机的续航时间，使实时航拍全天候侦查成为可能，具有广泛的应用前景。

Abstract

A defogging method of aerial image based on guided filter was proposed

and application of defogging system based on cloud computing in visual navigation and reconnaissance was realized. Firstly

atmospheric curtain function of aerial image was calculated by shadow channel

and edge preservation estimation of atmospheric curtain function was calculated by guided filter; then

residual image of original image and atmospheric curtain function were calculated and bright channel was extracted; finally reflection coefficient of scene was obtained according to light reflection model as recovered image. It wasn't needed to obtain global atmospheric light and better image details and overall visibility by guided filtering algorithm. The defogging method was implemented by powerful computing resources of cloud computing. Compared with traditional airborne processing system by unmanned aerial vehicle (UAV)

using powerful distributed computing power and massive storage capacity of cloud computing makes defogging system more efficient and quicker. It improves duration of flight of unmanned aerial vehicle

makes all-whether reconnaissance of real-time aerial photography become possible

and has extensive application prospect.

关键词

Keywords

references

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