IEICE TRANSACTIONS on Information
An Improved Single Image Haze Removal Algorithm Using Image Segmentation
Summary :
In this letter, we propose an improved single image haze removal algorithm using image segmentation. It can effectively resolve two common problems of conventional algorithms which are based on dark channel prior: halo artifact and wrong estimation of atmospheric light. The process flow of our algorithm is as follows. First, the input hazy image is over-segmented. Then, the segmentation results are used for improving the conventional dark channel computation which uses fixed local patches. Also, the segmentation results are used for accurately estimating the atmospheric light. Finally, from the improved dark channel and atmospheric light, an accurate transmission map is computed allowing us to recover a high quality haze-free image.
- Publication
- IEICE TRANSACTIONS on Information Vol.E97-D No.9 pp.2554-2558
- Publication Date
- 2014/09/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2014EDL8056
- Type of Manuscript
- LETTER
- Category
- Image Processing and Video Processing
Authors
Hanhoon PARK
Pukyong National University
Keyword
Latest Issue
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Hanhoon PARK, "An Improved Single Image Haze Removal Algorithm Using Image Segmentation" in IEICE TRANSACTIONS on Information,
vol. E97-D, no. 9, pp. 2554-2558, September 2014, doi: 10.1587/transinf.2014EDL8056.
Abstract: In this letter, we propose an improved single image haze removal algorithm using image segmentation. It can effectively resolve two common problems of conventional algorithms which are based on dark channel prior: halo artifact and wrong estimation of atmospheric light. The process flow of our algorithm is as follows. First, the input hazy image is over-segmented. Then, the segmentation results are used for improving the conventional dark channel computation which uses fixed local patches. Also, the segmentation results are used for accurately estimating the atmospheric light. Finally, from the improved dark channel and atmospheric light, an accurate transmission map is computed allowing us to recover a high quality haze-free image.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2014EDL8056/_p
Copy
@ARTICLE{e97-d_9_2554,
author={Hanhoon PARK, },
journal={IEICE TRANSACTIONS on Information},
title={An Improved Single Image Haze Removal Algorithm Using Image Segmentation},
year={2014},
volume={E97-D},
number={9},
pages={2554-2558},
abstract={In this letter, we propose an improved single image haze removal algorithm using image segmentation. It can effectively resolve two common problems of conventional algorithms which are based on dark channel prior: halo artifact and wrong estimation of atmospheric light. The process flow of our algorithm is as follows. First, the input hazy image is over-segmented. Then, the segmentation results are used for improving the conventional dark channel computation which uses fixed local patches. Also, the segmentation results are used for accurately estimating the atmospheric light. Finally, from the improved dark channel and atmospheric light, an accurate transmission map is computed allowing us to recover a high quality haze-free image.},
keywords={},
doi={10.1587/transinf.2014EDL8056},
ISSN={1745-1361},
month={September},}
Copy
TY - JOUR
TI - An Improved Single Image Haze Removal Algorithm Using Image Segmentation
T2 - IEICE TRANSACTIONS on Information
SP - 2554
EP - 2558
AU - Hanhoon PARK
PY - 2014
DO - 10.1587/transinf.2014EDL8056
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E97-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2014
AB - In this letter, we propose an improved single image haze removal algorithm using image segmentation. It can effectively resolve two common problems of conventional algorithms which are based on dark channel prior: halo artifact and wrong estimation of atmospheric light. The process flow of our algorithm is as follows. First, the input hazy image is over-segmented. Then, the segmentation results are used for improving the conventional dark channel computation which uses fixed local patches. Also, the segmentation results are used for accurately estimating the atmospheric light. Finally, from the improved dark channel and atmospheric light, an accurate transmission map is computed allowing us to recover a high quality haze-free image.
ER -
English
