Nighttime image dehazing with local atmospheric light and weighted entropy

Dubok Park; David K. Han; Hanseok Ko

doi:10.1109/ICIP.2016.7532761

Nighttime image dehazing with local atmospheric light and weighted entropy

Dubok Park
, David K. Han
, Hanseok Ko

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

20 Citations (Scopus)

Abstract

In this paper, we propose a novel framework for nighttime image dehazing based on a nighttime haze model which accounts for varying light sources and their glow. First, glow effects are decomposed using relative smoothness. Atmospheric light is then estimated by combining global and local atmospheric lights using a local atmospheric selection map. The transmission is estimated by maximizing an objective function designed with weighted entropy. Finally, haze is removed using two estimated parameters which are atmospheric light and transmission. Experimental results validate the proposed method can achieve haze-free results while alleviating the glow effect.

Original language	English
Title of host publication	2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
Publisher	IEEE Computer Society
Pages	2261-2265
Number of pages	5
Volume	2016-August
ISBN (Electronic)	9781467399616
DOIs	https://doi.org/10.1109/ICIP.2016.7532761
Publication status	Published - 2016 Aug 3
Event	23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States Duration: 2016 Sept 25 → 2016 Sept 28

Other

Other	23rd IEEE International Conference on Image Processing, ICIP 2016
Country/Territory	United States
City	Phoenix
Period	16/9/25 → 16/9/28

Keywords

Airlight
Dehazing
Layer separation
Transmission
Weighted entropy

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

Access to Document

10.1109/ICIP.2016.7532761

Cite this

Park, D, Han, DK & Ko, H 2016, Nighttime image dehazing with local atmospheric light and weighted entropy. in 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings. vol. 2016-August, 7532761, IEEE Computer Society, pp. 2261-2265, 23rd IEEE International Conference on Image Processing, ICIP 2016, Phoenix, United States, 16/9/25. https://doi.org/10.1109/ICIP.2016.7532761

@inproceedings{70ec35b29ce74f2db5120f99607a675c,

title = "Nighttime image dehazing with local atmospheric light and weighted entropy",

abstract = "In this paper, we propose a novel framework for nighttime image dehazing based on a nighttime haze model which accounts for varying light sources and their glow. First, glow effects are decomposed using relative smoothness. Atmospheric light is then estimated by combining global and local atmospheric lights using a local atmospheric selection map. The transmission is estimated by maximizing an objective function designed with weighted entropy. Finally, haze is removed using two estimated parameters which are atmospheric light and transmission. Experimental results validate the proposed method can achieve haze-free results while alleviating the glow effect.",

keywords = "Airlight, Dehazing, Layer separation, Transmission, Weighted entropy",

author = "Dubok Park and Han, \{David K.\} and Hanseok Ko",

year = "2016",

month = aug,

day = "3",

doi = "10.1109/ICIP.2016.7532761",

language = "English",

volume = "2016-August",

pages = "2261--2265",

booktitle = "2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings",

publisher = "IEEE Computer Society",

note = "23rd IEEE International Conference on Image Processing, ICIP 2016 ; Conference date: 25-09-2016 Through 28-09-2016",

}

TY - GEN

T1 - Nighttime image dehazing with local atmospheric light and weighted entropy

AU - Park, Dubok

AU - Han, David K.

AU - Ko, Hanseok

PY - 2016/8/3

Y1 - 2016/8/3

N2 - In this paper, we propose a novel framework for nighttime image dehazing based on a nighttime haze model which accounts for varying light sources and their glow. First, glow effects are decomposed using relative smoothness. Atmospheric light is then estimated by combining global and local atmospheric lights using a local atmospheric selection map. The transmission is estimated by maximizing an objective function designed with weighted entropy. Finally, haze is removed using two estimated parameters which are atmospheric light and transmission. Experimental results validate the proposed method can achieve haze-free results while alleviating the glow effect.

AB - In this paper, we propose a novel framework for nighttime image dehazing based on a nighttime haze model which accounts for varying light sources and their glow. First, glow effects are decomposed using relative smoothness. Atmospheric light is then estimated by combining global and local atmospheric lights using a local atmospheric selection map. The transmission is estimated by maximizing an objective function designed with weighted entropy. Finally, haze is removed using two estimated parameters which are atmospheric light and transmission. Experimental results validate the proposed method can achieve haze-free results while alleviating the glow effect.

KW - Airlight

KW - Dehazing

KW - Layer separation

KW - Transmission

KW - Weighted entropy

UR - https://www.scopus.com/pages/publications/85006809784

UR - https://www.scopus.com/pages/publications/85006809784#tab=citedBy

U2 - 10.1109/ICIP.2016.7532761

DO - 10.1109/ICIP.2016.7532761

M3 - Conference contribution

AN - SCOPUS:85006809784

VL - 2016-August

SP - 2261

EP - 2265

BT - 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings

PB - IEEE Computer Society

T2 - 23rd IEEE International Conference on Image Processing, ICIP 2016

Y2 - 25 September 2016 through 28 September 2016

ER -

Nighttime image dehazing with local atmospheric light and weighted entropy

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