Single image dehazing using a new color channel

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F21%3A50017706" target="_blank" >RIV/62690094:18450/21:50017706 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S1047320320302212?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1047320320302212?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jvcir.2020.103008" target="_blank" >10.1016/j.jvcir.2020.103008</a>

Result language

angličtina

Original language name

Single image dehazing using a new color channel

Original language description

Images with hazy scene suffer from low-contrast, which reduces the visible quality of the scene, thus making object detection a more challenging task. Low-contrast can result from foggy weather conditions during image acquisition. Dehazing is a process of removal of haze from the photography of a hazy scene. Single-image dehazing based on dark channel priors are well-known techniques in this field. However, the performance of such techniques is limited to priors or constraints. Moreover, this type of method fails when images have sky-region. So, a method is proposed, which can restore the visibility of hazy images. First, a hazy image is divided into blocks of size 32 × 32, then the score of each block is calculated to select a block having the highest score. Atmospheric light is calculated from the selected block. A new color channel is considered to remove atmospheric scattering, obtained channel value and atmospheric light are then used to calculate the transmission map in the second step. Third, radiance is computed using a transmission map and atmospheric light. The illumination scaling factor is adopted to enhance the quality of a dehazed image in the final step. Experiments are performed on six datasets namely, I-HAZE, O-HAZE, BSDS500, FRIDA, RESIDE dataset and natural images from Google. The proposed method is compared against 11 state-of-the-art methods. The performance is analyzed using fourteen quantitative evaluation metrics. All the results demonstrate that the proposed method outperforms 11 state-of-the-art methods in most of the cases. © 2020 Elsevier Inc.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20201 - Electrical and electronic engineering

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Visual Communication and Image Representation

ISSN

1047-3203

e-ISSN

—

Volume of the periodical

74

Issue of the periodical within the volume

JANUARY

Country of publishing house

US - UNITED STATES

Number of pages

16

Pages from-to

"Article number 103008"

UT code for WoS article

000620295500004

EID of the result in the Scopus database

2-s2.0-85099214977