Image quality improvement using local adaptive neighborhood-based dark channel prior

Toshiki Onoyama; Huimin Lu; Afzal Ahmed Soomro; Ainul Akmar Mokhtar; Tohru Kamiya; Seiichi Serikawa

doi:10.1117/12.2603771

Image quality improvement using local adaptive neighborhood-based dark channel prior

Toshiki Onoyama, Huimin Lu, Afzal Ahmed Soomro, Ainul Akmar Mokhtar, Tohru Kamiya, Seiichi Serikawa

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

Abstract

In-vehicle cameras and surveillance cameras are used in many situations in our daily lives. Visibility degradation in foggy environments is caused by the scattering of reflected light from real objects by minute water droplets or fog in the medium through which light passes. The degree of degradation depends on the density of suspended microparticles existing between the observed object and the observation point in the medium. In general, the farther the object is from the camera, the more it is affected by the fog. The purpose of image de-fogging is to improve the clarity of an object by removing the effects of fog in the image.

Original language	English
Title of host publication	International Symposium on Artificial Intelligence and Robotics 2021
Editors	Huimin Lu, Shenglin Mu, Shota Nakashima
Publisher	SPIE
ISBN (Electronic)	9781510646124
DOIs	https://doi.org/10.1117/12.2603771
State	Published - 2021
Externally published	Yes
Event	International Symposium on Artificial Intelligence and Robotics 2021 - Fukuoka, Japan Duration: 21 Aug 2021 → 27 Aug 2021

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	11884
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	International Symposium on Artificial Intelligence and Robotics 2021
Country/Territory	Japan
City	Fukuoka
Period	21/08/21 → 27/08/21

Bibliographical note

Publisher Copyright:
© 2021 SPIE.

Keywords

Dark channel prior
Dehazing
Local adaptive neighborhood

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.2603771

Cite this

Onoyama, T., Lu, H., Soomro, A. A., Mokhtar, A. A., Kamiya, T., & Serikawa, S. (2021). Image quality improvement using local adaptive neighborhood-based dark channel prior. In H. Lu, S. Mu, & S. Nakashima (Eds.), International Symposium on Artificial Intelligence and Robotics 2021 Article 118840M (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11884). SPIE. https://doi.org/10.1117/12.2603771

@inproceedings{327a5f6dc7db4f0e8b1a2bb0f81a30a7,

title = "Image quality improvement using local adaptive neighborhood-based dark channel prior",

abstract = "In-vehicle cameras and surveillance cameras are used in many situations in our daily lives. Visibility degradation in foggy environments is caused by the scattering of reflected light from real objects by minute water droplets or fog in the medium through which light passes. The degree of degradation depends on the density of suspended microparticles existing between the observed object and the observation point in the medium. In general, the farther the object is from the camera, the more it is affected by the fog. The purpose of image de-fogging is to improve the clarity of an object by removing the effects of fog in the image.",

keywords = "Dark channel prior, Dehazing, Local adaptive neighborhood",

author = "Toshiki Onoyama and Huimin Lu and Soomro, \{Afzal Ahmed\} and Mokhtar, \{Ainul Akmar\} and Tohru Kamiya and Seiichi Serikawa",

note = "Publisher Copyright: {\textcopyright} 2021 SPIE.; International Symposium on Artificial Intelligence and Robotics 2021 ; Conference date: 21-08-2021 Through 27-08-2021",

year = "2021",

doi = "10.1117/12.2603771",

language = "English",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE",

editor = "Huimin Lu and Shenglin Mu and Shota Nakashima",

booktitle = "International Symposium on Artificial Intelligence and Robotics 2021",

address = "United States",

}

Onoyama, T, Lu, H, Soomro, AA, Mokhtar, AA, Kamiya, T & Serikawa, S 2021, Image quality improvement using local adaptive neighborhood-based dark channel prior. in H Lu, S Mu & S Nakashima (eds), International Symposium on Artificial Intelligence and Robotics 2021., 118840M, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11884, SPIE, International Symposium on Artificial Intelligence and Robotics 2021, Fukuoka, Japan, 21/08/21. https://doi.org/10.1117/12.2603771

Image quality improvement using local adaptive neighborhood-based dark channel prior. / Onoyama, Toshiki; Lu, Huimin; Soomro, Afzal Ahmed et al.
International Symposium on Artificial Intelligence and Robotics 2021. ed. / Huimin Lu; Shenglin Mu; Shota Nakashima. SPIE, 2021. 118840M (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11884).

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

TY - GEN

T1 - Image quality improvement using local adaptive neighborhood-based dark channel prior

AU - Onoyama, Toshiki

AU - Lu, Huimin

AU - Soomro, Afzal Ahmed

AU - Mokhtar, Ainul Akmar

AU - Kamiya, Tohru

AU - Serikawa, Seiichi

PY - 2021

Y1 - 2021

N2 - In-vehicle cameras and surveillance cameras are used in many situations in our daily lives. Visibility degradation in foggy environments is caused by the scattering of reflected light from real objects by minute water droplets or fog in the medium through which light passes. The degree of degradation depends on the density of suspended microparticles existing between the observed object and the observation point in the medium. In general, the farther the object is from the camera, the more it is affected by the fog. The purpose of image de-fogging is to improve the clarity of an object by removing the effects of fog in the image.

AB - In-vehicle cameras and surveillance cameras are used in many situations in our daily lives. Visibility degradation in foggy environments is caused by the scattering of reflected light from real objects by minute water droplets or fog in the medium through which light passes. The degree of degradation depends on the density of suspended microparticles existing between the observed object and the observation point in the medium. In general, the farther the object is from the camera, the more it is affected by the fog. The purpose of image de-fogging is to improve the clarity of an object by removing the effects of fog in the image.

KW - Dark channel prior

KW - Dehazing

KW - Local adaptive neighborhood

UR - https://www.scopus.com/pages/publications/85120496362

U2 - 10.1117/12.2603771

DO - 10.1117/12.2603771

M3 - Conference contribution

AN - SCOPUS:85120496362

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - International Symposium on Artificial Intelligence and Robotics 2021

A2 - Lu, Huimin

A2 - Mu, Shenglin

A2 - Nakashima, Shota

PB - SPIE

T2 - International Symposium on Artificial Intelligence and Robotics 2021

Y2 - 21 August 2021 through 27 August 2021

ER -

Onoyama T, Lu H, Soomro AA, Mokhtar AA, Kamiya T, Serikawa S. Image quality improvement using local adaptive neighborhood-based dark channel prior. In Lu H, Mu S, Nakashima S, editors, International Symposium on Artificial Intelligence and Robotics 2021. SPIE. 2021. 118840M. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2603771

Image quality improvement using local adaptive neighborhood-based dark channel prior

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this