Volume 10 Number 2(Jun. 2018)
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IJCEE 2018 Vol.10(2): 146-157 ISSN: 1793-8163
DOI: 10.17706/IJCEE.2018.10.2.146-157

Feature-Centric Image Enhancement via Dehazing

Prince Owusu-Agyeman, Xie Wei, Yao Yeboah
Abstract—In this paper, we address the image dehazing problem through a global feature-restoration pipeline. We propose a dark channel prior-based global image dehazing algorithm which captures and restores the true features of pixels within haze-degraded regions by applying scene depth selection and adaptive filtering. Our scheme harnesses haze and depth features intuitively across a given image without the prior scene depth information. This allows our scheme to sustain a high dehazing efficiency across all image regions irrespective of the local depth variations. We prove that haze degradation is linearly correlated with scene depth and based on this nuance, propose a depth selection and cropping scheme, which guides the adaptive filter iteratively across the image. Secondly, we put forward haze relevant image features and highlight the dark-channel prior for image dehazing. We merge the dark channel prior and scene depth-cropping schemes into a unified dehazing pipeline which is capable of sustaining uniform and robust results across all image regions, in real-time. We verify the superiority of the proposed scheme in terms of speed and robustness through computer-based experiments. Finally, we present comparison results with state-of-the-art and further highlight the comparative superiority of our scheme.

Index Terms—Dark channel prior, real-time dehazing, feature restoration, image enhancement.

Prince Owusu-Agyeman, Xie Wei and Yao Yeboah are with School of Automation Science and Engineering, Guangdong University of Technology, Guangzhou, P.R. China.

Cite:Prince Owusu-Agyeman, Xie Wei, Yao Yeboah, "Feature-Centric Image Enhancement via Dehazing," International Journal of Computer and Electrical Engineering vol. 10, no. 2, pp. 146-157, 2018.

General Information

ISSN: 1793-8163
Frequency: Quarterly
Editor-in-Chief: Prof. Yucong Duan
Abstracting/ Indexing: EI (INSPEC, IET), Ulrich's Periodicals Directory, Google Scholar, EBSCO, ProQuest, and Electronic Journals Library
E-mail: ijcee@iap.org

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