Fast single image dehazing method based on illumination veil elimination

LI Da-jian; SUN Wei; PAN Rong

doi:10.3788/OPE.20162413.0622

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Fast single image dehazing method based on illumination veil elimination

更新时间：2020-08-13

- Fast single image dehazing method based on illumination veil elimination
- Optics and Precision Engineering Vol. 24, Issue 10s, Pages: 622-631(2016)
- 作者机构：
  
  1. 西安电子科技大学空间科学与技术学院,陕西西安,710118
  2. 西北工业大学第365研究所西安,710065
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20162413.0622
  CLC： TP394.1;TH691.9
- Received：19 April 2016，
  
  Revised：03 June 2016，
  
  Published：14 November 2016
- 稿件说明：
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李大健, 孙伟, 潘蓉. 光照分量去除的单幅图像快速去雾方法[J]. 光学精密工程, 2016,24(10s): 622-631

LI Da-jian, SUN Wei, PAN Rong. Fast single image dehazing method based on illumination veil elimination[J]. Editorial Office of Optics and Precision Engineering, 2016,24(10s): 622-631
李大健, 孙伟, 潘蓉. 光照分量去除的单幅图像快速去雾方法[J]. 光学精密工程, 2016,24(10s): 622-631 DOI： 10.3788/OPE.20162413.0622.

LI Da-jian, SUN Wei, PAN Rong. Fast single image dehazing method based on illumination veil elimination[J]. Editorial Office of Optics and Precision Engineering, 2016,24(10s): 622-631 DOI： 10.3788/OPE.20162413.0622.

摘要

基于大气散射物理模型，提出了一种全新的将雾霾去除和光照恢复统一的有雾图像复原方法。首先基于暗影通道原理求取大气幕函数，获得去除大气幕后的残差图像；然后基于光照-反射成像模型和亮通道概念，通过联合双边滤波有效地获取残差图像光照分量信息；最后，去除残差图像的光照分量，从而获得了与光照无关的场景物体反射分量，同时去除了雾霾和光照对成像过程的影响。和传统的基于暗影通道的方法相比，本方法无需求解全局环境光的值与透射率函数，通过两个步骤即可复原场景的RGB反射系数。本方法再现的场景颜色饱和度适中，获得了生动的颜色再现并避免光晕伪影。

Abstract

An unified approach based on atmospheric scattering model is proposed to handle such degraded images with the strategy that gracefully bridges the gap between un-uniform illumination and hazy images. According to dark channel principle

the atmospheric veil function is caculated

and the residual image removing atmospheric veil is obtained. Then

based on illumination-reflection model and bright channel theory

with joint bilateral filter

illumination component of residual image is obtained and removed. So the reflection components which has nothing to do with illumination is obtained. Meanwhile

influence of hazy and illumination is removed. The proposed approach simultaneously dehazes images and enhances contrast

and the global atmospheric light is not necessary to be calculated to avoid the risk of errors. Experiment results on a variety of outdoor degraded images demonstrate that the proposed method achieves short computation time and good restoration for visibility and color fidelity.

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Keywords

references

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