Enhancement of image degraded by fog using cost function based on human visual model

Dongjun Kim; Changwon Jeon; Bonghyup Kang; Hanseok Ko

doi:10.1007/978-3-540-89859-7_12

Enhancement of image degraded by fog using cost function based on human visual model

Dongjun Kim, Changwon Jeon, Bonghyup Kang, Hanseok Ko

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

7 Citations (Scopus)

Abstract

In foggy weather conditions, images become degraded due to the presence of airlight that is generated by scattering light by fog particles. In this paper, we propose an effective method to correct the degraded image by subtracting the estimated airlight map from the degraded image. The airlight map is generated using multiple linear regression, which models the relationship between regional airlight and the coordinates of the image pixels. Airlight can then be estimated using a cost function that is based on the human visual model, wherein a human is more insensitive to variations of the luminance in bright regions than in dark regions. For this objective, the luminance image is employed for airlight estimation. The luminance image is generated by an appropriate fusion of the R, G, and B components. Representative experiments on real foggy images confirm significant enhancement in image quality over the degraded image.

Original language	English
Title of host publication	Multisensor Fusion and Integration for Intelligent Systems
Subtitle of host publication	An Edition of the Selected Papers from the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2008
Pages	163-171
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-540-89859-7_12
Publication status	Published - 2009
Event	7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI 2008 - Seoul, Korea, Republic of Duration: 2008 Aug 20 → 2008 Aug 22

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	35 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Other

Other	7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI 2008
Country/Territory	Korea, Republic of
City	Seoul
Period	08/8/20 → 08/8/22

ASJC Scopus subject areas

Industrial and Manufacturing Engineering

Access to Document

10.1007/978-3-540-89859-7_12

Cite this

Kim, D., Jeon, C., Kang, B., & Ko, H. (2009). Enhancement of image degraded by fog using cost function based on human visual model. In Multisensor Fusion and Integration for Intelligent Systems: An Edition of the Selected Papers from the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2008 (pp. 163-171). (Lecture Notes in Electrical Engineering; Vol. 35 LNEE). https://doi.org/10.1007/978-3-540-89859-7_12

Enhancement of image degraded by fog using cost function based on human visual model. / Kim, Dongjun; Jeon, Changwon; Kang, Bonghyup et al.
Multisensor Fusion and Integration for Intelligent Systems: An Edition of the Selected Papers from the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2008. 2009. p. 163-171 (Lecture Notes in Electrical Engineering; Vol. 35 LNEE).

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

Kim, D, Jeon, C, Kang, B & Ko, H 2009, Enhancement of image degraded by fog using cost function based on human visual model. in Multisensor Fusion and Integration for Intelligent Systems: An Edition of the Selected Papers from the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2008. Lecture Notes in Electrical Engineering, vol. 35 LNEE, pp. 163-171, 7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI 2008, Seoul, Korea, Republic of, 08/8/20. https://doi.org/10.1007/978-3-540-89859-7_12

Kim D, Jeon C, Kang B, Ko H. Enhancement of image degraded by fog using cost function based on human visual model. In Multisensor Fusion and Integration for Intelligent Systems: An Edition of the Selected Papers from the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2008. 2009. p. 163-171. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-3-540-89859-7_12

Kim, Dongjun ; Jeon, Changwon ; Kang, Bonghyup et al. / Enhancement of image degraded by fog using cost function based on human visual model. Multisensor Fusion and Integration for Intelligent Systems: An Edition of the Selected Papers from the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2008. 2009. pp. 163-171 (Lecture Notes in Electrical Engineering).

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title = "Enhancement of image degraded by fog using cost function based on human visual model",

abstract = "In foggy weather conditions, images become degraded due to the presence of airlight that is generated by scattering light by fog particles. In this paper, we propose an effective method to correct the degraded image by subtracting the estimated airlight map from the degraded image. The airlight map is generated using multiple linear regression, which models the relationship between regional airlight and the coordinates of the image pixels. Airlight can then be estimated using a cost function that is based on the human visual model, wherein a human is more insensitive to variations of the luminance in bright regions than in dark regions. For this objective, the luminance image is employed for airlight estimation. The luminance image is generated by an appropriate fusion of the R, G, and B components. Representative experiments on real foggy images confirm significant enhancement in image quality over the degraded image.",

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AB - In foggy weather conditions, images become degraded due to the presence of airlight that is generated by scattering light by fog particles. In this paper, we propose an effective method to correct the degraded image by subtracting the estimated airlight map from the degraded image. The airlight map is generated using multiple linear regression, which models the relationship between regional airlight and the coordinates of the image pixels. Airlight can then be estimated using a cost function that is based on the human visual model, wherein a human is more insensitive to variations of the luminance in bright regions than in dark regions. For this objective, the luminance image is employed for airlight estimation. The luminance image is generated by an appropriate fusion of the R, G, and B components. Representative experiments on real foggy images confirm significant enhancement in image quality over the degraded image.

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Enhancement of image degraded by fog using cost function based on human visual model

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