Abstract
Poor visibility in the presence of fog is a major problem for many applications of computer vision. Still image and video systems are typically of limited use in poor visibility condition as the degraded images/frames lack visual vividness and offer low visibility of the scene contents. This paper investigates the defogging effects on images and frames by using a fast defogging method on our own newly developed database, namely Society of Applied Microwave Electronics Engineering and Research-Tripura University (SAMEER-TU) database which consists of 5,390 color images and 10 videos captured in foggy as well as in clear condition. The first step of the method ensures contrast enhancement yielding better global visibility, but the images/frames containing very dense fog still suffer from low visibility. In that case, Luminance and chromatic weight map have been used. Finally for verifying the robustness of the method, qualitative assessment evaluation in respect of peak-signal-to-noise ratio (PSNR) and root-mean-square error (RMSE) is introduced as a contributory step in this paper.
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Acknowledgments
The first author is thankful to the Society of Applied Microwave Electronics Engineering and Research (SAMEER), R&D Lab of Department of Electronics and Information Technology (DeitY), Government of India. The database presented here is being created in the Biometrics Laboratory of Department of Computer Science and Engineering of Tripura University (A Central University), India, under the project entitled “Development of Thermography Infrastructure facility for Security and Navigation System-Phase-1” supported by the Grant No. SMR/PD(R)/NER/2012–13/Thermography, dated 22/03/2013 from the Society of Applied Microwave Electronics Engineering and Research (SAMEER), IIT Bombay campus, Powai, Mumbai 400076.
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Pal, T., Bhowmik, M.K., Ghosh, A.K. (2015). Contrast Restoration of Fog-Degraded Image Sequences. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 335. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2217-0_28
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DOI: https://doi.org/10.1007/978-81-322-2217-0_28
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