Abstract
Images captured under foggy conditions often exhibit poor contrast and color. This is primarily due to the air-light which degrades image quality exponentially with fog depth between the scene and the camera. In this paper, we restore fog-degraded images by first estimating depth using the physical model characterizing the RGB channels in a single monocular image. The fog effects are then removed by subtracting the estimated irradiance, which is empirically related to the scene depth information obtained, from the total irradiance received by the sensor. Effective restoration of color and contrast of images taken under foggy conditions are demonstrated. In the experiments, we validate the effectiveness of our method compared with conventional method.
| Original language | English |
|---|---|
| Pages (from-to) | 1793-1799 |
| Number of pages | 7 |
| Journal | IEICE Transactions on Information and Systems |
| Volume | E96-D |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 2013 Aug 27 |
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Keywords
- Air-light
- De-hazing
- Depth estimation
- Image restoration
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Software
- Artificial Intelligence
- Hardware and Architecture
- Computer Vision and Pattern Recognition
Cite this
Fast single image de-hazing using characteristics of RGB channel of foggy image. / Park, Dubok; Han, David K.; Jeon, Changwon; Ko, Hanseok.
In: IEICE Transactions on Information and Systems, Vol. E96-D, No. 8, 27.08.2013, p. 1793-1799.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Fast single image de-hazing using characteristics of RGB channel of foggy image
AU - Park, Dubok
AU - Han, David K.
AU - Jeon, Changwon
AU - Ko, Hanseok
PY - 2013/8/27
Y1 - 2013/8/27
N2 - Images captured under foggy conditions often exhibit poor contrast and color. This is primarily due to the air-light which degrades image quality exponentially with fog depth between the scene and the camera. In this paper, we restore fog-degraded images by first estimating depth using the physical model characterizing the RGB channels in a single monocular image. The fog effects are then removed by subtracting the estimated irradiance, which is empirically related to the scene depth information obtained, from the total irradiance received by the sensor. Effective restoration of color and contrast of images taken under foggy conditions are demonstrated. In the experiments, we validate the effectiveness of our method compared with conventional method.
AB - Images captured under foggy conditions often exhibit poor contrast and color. This is primarily due to the air-light which degrades image quality exponentially with fog depth between the scene and the camera. In this paper, we restore fog-degraded images by first estimating depth using the physical model characterizing the RGB channels in a single monocular image. The fog effects are then removed by subtracting the estimated irradiance, which is empirically related to the scene depth information obtained, from the total irradiance received by the sensor. Effective restoration of color and contrast of images taken under foggy conditions are demonstrated. In the experiments, we validate the effectiveness of our method compared with conventional method.
KW - Air-light
KW - De-hazing
KW - Depth estimation
KW - Image restoration
UR - http://www.scopus.com/inward/record.url?scp=84882597238&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84882597238&partnerID=8YFLogxK
U2 - 10.1587/transinf.E96.D.1793
DO - 10.1587/transinf.E96.D.1793
M3 - Article
VL - E96-D
SP - 1793
EP - 1799
JO - IEICE Transactions on Information and Systems
JF - IEICE Transactions on Information and Systems
SN - 0916-8532
IS - 8
ER -