光照分量去除的单幅图像快速去雾方法

李大健; 孙伟; 潘蓉

doi:10.3788/OPE.20162413.0622

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光照分量去除的单幅图像快速去雾方法

更新时间：2020-08-13

- 光照分量去除的单幅图像快速去雾方法
- Fast single image dehazing method based on illumination veil elimination
- 光学精密工程 2016年24卷第10s期页码：622-631
- 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：
  
  国家自然科学基金青年项目《视觉原理指导下的动目标检测与跟踪新方法研究》（No.61201290）();国家自然科学基金面上资助项目《基于视觉仿生的无人机环境感知关键技术
- DOI：10.3788/OPE.20162413.0622
  中图分类号： TP394.1;TH691.9
- 收稿日期：2016-04-19，
  
  修回日期：2016-06-03，
  
  纸质出版日期：2016-11-14
- 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.

关键词

Keywords

references

TAN K, OAKLEY P J. Physics-based approach to color image enhancement in poor visibility conditions[J].Optical Society of America, 2001, 18(10):2460-2467.

FATTAL R. Single image dehazing[J].ACM Transactions on Graphics, 2008, 27(3):1-9.

TAREL J P, HAYTUERE N. Fast visibility restoration from a single color or gray level image[C]. Proceedings of the 12th IEEE International Conference on Computer Vision, Kyoto.Japan:IEEE, 2009:2201-2208.

HE K M,SUN J,TANG X O. Single image haze removal using dark channel prior[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Miami. USA:IEEE, 2009:1956-1963.

KOPF J, NEUBERT B, CHEN B, et al.. Deep photo:model-based photograph enhancement and viewing'[J]. ACM Trans. Graph., 2008, 27(5), 116-1-116-10.

ANCUTI C, HERMANS C, BEKAERT P. A fast semi-inverse approach to detect and remove the haze from a single image[C]. Proc. ACCV, 2011:501-514.

KIM J H, JANG W D, SIM J Y, et al.. Optimized contrast enhancement for real-time image and video dehazing[J].Journal of Visual Communication and Image Representation, 2013,24(3):410-425.

TRIPATHI A K, MUKHOPADHYAY S. Single image fog removal using anisotropic diffusion[J]. IET Image processing, 2012, 6(7):966-975.

NARASIMHAN S G, NAYAR S K. Contrast restoration of weather degraded images[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(6):713-724.

TAN R C. Visibility in bad weather from a single image[C].IEEE Conference on Computer Vision and Pattern Recognition (CVPR'08), 2008, 1-8.

XIAO C, GAN J. Fast image dehazing using guided joint bilateral filter[J].The Visual Computer, 2012, 28(6-8):713-721.

RAHMAN, Z U, JOBSON D J. Retinex processing for automatic image enhancement[J]. Journal of Electronic Imaging,2004,13(1):100-110.

SHUKRI D S M,ASMUNI H, OTHMAN R M, et al.. An improved multiscale retinex algorithm for motion-blurred iris images to minimize the intra-individual variations[J]. Pattern Recognition Letters,2013,34(9):1071-1077.

CHAO W H, LAI A Y, SHIH Y Y I, et al.. Correction of inhomogeneous magnetic resonance images using multiscale retinex for segmentation accuracy improvement[J].Biomedical Signal Processing and Control, 2012,7(2):129-140.

HASHEMI S, KIANI S, NOROOZI N, et al.. An image contrast enhancement method based on genetic algorithm[J]. Pattern Recognition Letters,2010,31(13):1816-1824.

HUANG S C, YEH C H. Image contrast enhancement for preserving mean brightness without losing image features[J].Engineering Applications of Artificial Intelligence, 2013, 26(5):1487-1492.

PARIS S, DURAND F. A fast approximation of the bilateral filter using a signal processing approach[C]. Computer Vision-ECCV 2006, Springer Berlin Heidelberg, 2006:568-580.

ZHANG B Y, ALLEBACH J P. Adaptive bilateral filter for sharpness enhancement and noise removal[J]. IEEE Transactions on Image Processing, 2008,17(5):664-678.

SUN CH H, DUAN H B. A restricted-direction target search approach based on coupled routing and optical sensor tasking optimization[J]. OPTIK, 2012, 123(24):2226-2229.

HAUTIRE N. Blind contrast enhancement assessment by gradient ratioing at visible edges[J]. Image Analysis & Stereology, 2008, 27(2):87-95.

HE K M, SUN J, TANG X O. Guided image filtering[C]. Computer Vision-ECCV 2010. Springer Berlin Heidelberg, 2010:1-14.

SCHECHNER Y Y, NARASIMHAN S G, NAYAR S K. Polarization-based vision through haze[J]. Applied Optics, 2003, 42(3):511-525.

NARASIMHAN S G, NAYAR S K. Vision and the atmosphere[J].International Journal of Computer Vision, 2002, 48(3):233-254.

GARG K, NAYAR S K. Vision and rain[J]. Int. J. Comput. Vis.2007, 75(1):3-27.

YEH C H, KANG L W, LEE M S,et al.. Haze effect removal from image via haze density estimation in optical model[J]. Optics Express, 2013,21(22):27127-27141.

BAI Y, LI C, JIA W, et al.. Designing a wearable computer for lifestyle evaluation[C]. 38th Annual Northeast Bioengineering Conference, 2012 March 16-18:243-244.

WEI S,GUO B L. A fast single-image dehazing method for visible-light systems[J].Optical Engineering, 2013,52(9):093103.

WEI S. A new single image fog removal algorithm based on physical model[J]. International Journal for Light and Electron Optics, 2013, 124(21):4770-4775.

SUN W, HAN L, GUO B L. A fast color image enhancement algorithm based on max intensity channel[J]. Journal of Modern Optics, 2014, 61(6):466-477.

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