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Image smog restoration using oblique gradient profile prior and energy minimization

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Abstract

Removing the smog from digital images is a challenging pre-processing tool in various imaging systems. Therefore, many smog removal (i.e., desmogging) models are proposed so far to remove the effect of smog from images. The desmogging models are based upon a physical model, it means it requires efficient estimation of transmission map and atmospheric veil from a single smoggy image. Therefore, many prior based restoration models are proposed in the literature to estimate the transmission map and an atmospheric veil. However, these models utilized computationally extensive minimization of an energy function. Also, the existing restoration models suffer from various issues such as distortion of texture, edges, and colors. Therefore, in this paper, a convolutional neural network (CNN) is used to estimate the physical attributes of smoggy images. Oblique gradient channel prior (OGCP) is utilized to restore the smoggy images. Initially, a dataset of smoggy and sunny images are obtained. Thereafter, we have trained CNN to estimate the smog gradient from smoggy images. Finally, based upon the computed smog gradient, OGCP is utilized to restore the still smoggy images. Performance analyses reveal that the proposed CNN-OGCP based desmogging model outperforms the existing desmogging models in terms of various performance metrics.

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Acknowledgements

The authors would like to thank their organizations especially Teerthanker Mahaveer University, Moradabad, India to provide suitable time and resources to successfully finish this research work.

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Authors and Affiliations

  1. College of Computing Science and Information Technogy, Teerthanker Mahaveer University, Moradabad, 244001, India

    Ashok Kumar & Arpit Jain

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  1. Ashok Kumar
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  2. Arpit Jain
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Correspondence to Arpit Jain.

Additional information

Ashok Kumar received the PhD in Computer Science from Gurukula Kangri Vishwavidyalaya Haridwar, India in 2019 and Master’s degree in Computer Applications from Dr. Bhim Rao Ambedkar University Agra, India in 2002. He is an associate professor at the College of Computing Science and Information Technology, Teerthanker Mahaveer University Moradabad, India. He has authored 20 research papers in the International/National Journals and Conferences.

Arpit Jain has competent, diligent & result oriented professional, offering over 16+ years of exposure across teaching in the field of Computer Science; currently spearheading as associate professor with Teerthanker Mahaveer University, India. He received the B Tech degree from UPTU, India in 2006, the M Tech degree from Shobhit Universirt, India and the PhD degrees from the Teerthanker Mahaveer University, India, all in Computer Science and Engineering. His current research interests are in the area of image processing, chip implementation by introducing the concept of Machine learning.

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Kumar, A., Jain, A. Image smog restoration using oblique gradient profile prior and energy minimization. Front. Comput. Sci. 15, 156706 (2021). https://doi.org/10.1007/s11704-020-9305-8

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