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Improved image defogging method and its application in video monitoring system based on ARM

Haijiang Zhu (College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China)
Xiupu Yin (College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China)
Xuan Wang (College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China)

Sensor Review

ISSN: 0260-2288

Article publication date: 10 June 2014

153

Abstract

Purpose

The purpose of this paper is to improve an image defogging algorithm based on a dark channel prior and use this method to clear the foggy image on the Advanced RISC (Reduced Instruction Set Computing) Machines (ARM) platform.

Design/methodology/approach

The divided strategy of the foggy image was proposed through the estimation of the brightness and transmission thresholds. The two regions of the foggy image were processed using two transmissions. Many foggy images were tested using the improved method.

Findings

The finding resulting from this study is that a divided strategy has been proposed to use the image defogging. Compared with the existing methods, the running time of the improved method is less on the ARM platform.

Practical implications

Image enhancement is an important technology of digital images, and the quality of images plays a key role in the video monitoring and the intelligent transportation system.

Originality/value

This paper presented an improved image defogging method using the divided strategy and a substantial number of experimental results was provided to demonstrate this method.

Keywords

Acknowledgements

This work was supported by the Beijing University of Chemical Technology Interdisciplinary Funds for “Visual Media Computing” and Beijing Training Programme Foundation for the Talents No.2012B009016000004.

Citation

Zhu, H., Yin, X. and Wang, X. (2014), "Improved image defogging method and its application in video monitoring system based on ARM", Sensor Review, Vol. 34 No. 3, pp. 266-272. https://doi.org/10.1108/SR-05-2012-684

Publisher

:

Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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