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Desmogging of still images using residual regression network and morphological erosion

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Abstract

Smog is one of the air pollutants that makes it difficult for drivers to see. Smog is a mixture of fog and smoke that produces black fumes and reduces the visibility of drivers within the range of one kilometre. The small size and high density of smog particles, in comparison to other air pollutants, impede drivers’ vision on the road. To resolve these problems, researchers designed a number of visibility restoration models. However, the development of an adequate desmogging technique is a challenging issue. The aerial and sensing imaging of machine vision systems are modified by the desmogging model. In this paper, a residual regression network (RRNet) is proposed followed by morphological erosion to produce a transmission map. The atmospheric light is estimated by using a 2D order statistic filter. The smoggy image is further reconstructed to obtain the clear scene radiance. Thus, the proposed model has a susceptibility to remove smog from road images in an effective manner. The proposed model is evaluated on the four well-known benchmark datasets and compared with five well-known desmogging techniques. The performance of the proposed desmogging model is evaluated in terms of color deviation, structure similarity index, and peak signal to noise ratio. It is found superior as compared to the existing models in terms of various performance metrics namely, fog aware density evaluation, naturalness image quality evaluator, perception-based image-quality, blind/referenceless image spatial quality evaluator, and image entropy by 2.2%, 1.17%, 8.05%, 2.64%, and 0.69% respectively.

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Acknowledgements

This research is supported by Council of Scientific and Industrial Research (CSIR), India. The sanction number of the scheme is 22(0801)/19/EMR-II.

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Authors and Affiliations

  1. Department of Electrical and Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala, India

    Akshay Juneja & Sunil Kumar Singla

  2. Department of Information Technology, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, India

    Vijay Kumar

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  1. Akshay Juneja
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Correspondence to Vijay Kumar.

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Juneja, A., Kumar, V. & Singla, S.K. Desmogging of still images using residual regression network and morphological erosion. Multimed Tools Appl 83, 7179–7214 (2024). https://doi.org/10.1007/s11042-023-15893-x

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