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2015 | OriginalPaper | Chapter

Contrast Restoration of Fog-Degraded Image Sequences

Authors : Tannistha Pal, Mrinal Kanti Bhowmik, Anjan Kumar Ghosh

Published in: Proceedings of Fourth International Conference on Soft Computing for Problem Solving

Publisher: Springer India

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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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Metadata
Title
Contrast Restoration of Fog-Degraded Image Sequences
Authors
Tannistha Pal
Mrinal Kanti Bhowmik
Anjan Kumar Ghosh
Copyright Year
2015
Publisher
Springer India
Book
Proceedings of Fourth International Conference on Soft Computing for Problem Solving

Print ISBN: 978-81-322-2216-3

Electronic ISBN: 978-81-322-2217-0

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-81-322-2217-0_28

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