Abstract
The meteorological visibility estimation is an important task, for example, in road traffic control and aviation safety, but its reliable automation is difficult. The conventional light scattering measurements are limited into a small space and the extrapolated values are often erroneous. The current meteorological visibility estimates relying on a single camera work only with data captured in day light. We propose a new method based on feature vectors that are projections of the scene images with lighting normalization. The proposed method was combined with the high dynamic range imaging to improve night time image quality. Visibility classification accuracy (F1) of 85.5 % was achieved for data containing both day and night images. The results show that the approach can compete with commercial visibility measurement devices.
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Notes
- 1.
The data and Matlab implementation are available upon a request from the authors.
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Acknowledgment
The Finnish meteorological institute is acknowledged for both the image data and the reference data used in the HDR experiments. Nicolas Hautière and Éric Dumont are thanked for the Matilda database. Eliska Nyrönen is acknowledged for the implementation of the regression model based method described in [5].
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Varjo, S., Hannuksela, J. (2015). Image Based Visibility Estimation During Day and Night. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9010. Springer, Cham. https://doi.org/10.1007/978-3-319-16634-6_21
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DOI: https://doi.org/10.1007/978-3-319-16634-6_21
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