Abstract
In the field of image processing, analyzing fog-affected images is challenging, as their visibility is degraded. In the absence of state-of-the-art image processing techniques to mitigate the impact of high-density fog, an adaptive-function-based image-defogging technique is proposed in this paper. The proposed technique accurately enhances such degraded images by adjusting the contrast and brightness based on a suitable threshold operator. The images are subsequently characterized as foggy or non-foggy on the basis of objective evaluation. The experimental results have proven that the proposed method achieves superior performance in terms of qualitative evaluation on non-reference metric (i.e., in terms of e = 0.468, σ = 0, r = 1.8857) and reference metric (i.e. in terms of MSE = 1580, PSNR = 19.2126, NCC = 0.4873, SC = 0.4684, MD = 60, NAE = 0.2229) compared with nine state-of-the-art dehazing methods. Furthermore, based on the average computational time achieved by the proposed method (0.36 s using a test set of 2000 images), it can be highly suitable for real-time applications.
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The work depicted here has been funded in part by the Grant no: SMR/PD(R)/NER/2012–13/Thermography,Dated 22/03/2013 from the Society of Applied Microwave Electronics Engineering & Research (SAMEER), IIT Bombay, India.
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Tannistha Pal- formal analysis, methodology, validation, data curation, writing. Debotosh Bhattacharjee-conceptualization, Review & Editing, visualization, supervision
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Pal, T., Bhattacharjee, D. Visibility enhancement of fog degraded images using adaptive defogging function. Multimed Tools Appl 81, 35317–35347 (2022). https://doi.org/10.1007/s11042-022-12182-x
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DOI: https://doi.org/10.1007/s11042-022-12182-x