Abstract
Stereo reconstruction serves many outdoor applications, and thus sometimes faces foggy weather. The quality of the reconstruction by state of the art algorithms is then degraded as contrast is reduced with the distance because of scattering. However, as shown by defogging algorithms from a single image, fog provides an extra depth cue in the gray level of far away objects. Our idea is thus to take advantage of both stereo and atmospheric veil depth cues to achieve better stereo reconstructions in foggy weather. To our knowledge, this subject has never been investigated earlier by the computer vision community. We thus propose a Markov Random Field model of the stereo reconstruction and defogging problem which can be optimized iteratively using the α-expansion algorithm. Outputs are a dense disparity map and an image where contrast is restored. The proposed model is evaluated on synthetic images. This evaluation shows that the proposed method achieves very good results on both stereo reconstruction and defogging compared to standard stereo reconstruction and single image defogging.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 1222–1239 (2001)
Woodford, O., Torr, P., Reid, I., Fitzgibbon, A.: Global stereo reconstruction under second-order smoothness priors. IEEE Transactions on Pattern Analysis Machine Intelligence 31, 2115–2128 (2009)
Geiger, A., Roser, M., Urtasun, R.: Efficient Large-Scale Stereo Matching. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part I. LNCS, vol. 6492, pp. 25–38. Springer, Heidelberg (2011)
Nishino, K., Kratz, L., Lombardi, S.: Bayesian defogging. International Journal of Computer Vision 98, 263–278 (2012)
Hautière, N., Tarel, J.-P., Lavenant, J., Aubert, D.: Automatic fog detection and estimation of visibility distance through use of an onboard camera. Machine Vision and Applications 17, 8–20 (2006)
Tarel, J.-P., Hautière, N.: Fast visibility restoration from a single color or gray level image. In: Proceedings of IEEE International Conference on Computer Vision (ICCV 2009), Kyoto, Japan, pp. 2201–2208 (2009)
Tarel, J.-P., Hautière, N., Caraffa, L., Cord, A., Halmaoui, H., Gruyer, D.: Vision enhancement in homogeneous and heterogeneous fog. IEEE Intelligent Transportation Systems Magazine 4, 6–20 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Caraffa, L., Tarel, JP. (2013). Stereo Reconstruction and Contrast Restoration in Daytime Fog. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7727. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37447-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-37447-0_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37446-3
Online ISBN: 978-3-642-37447-0
eBook Packages: Computer ScienceComputer Science (R0)