A Survey on Image and Video Dehazing

Authors

  • Thomas A PG Scholar, Met’s School of engineering, Calicut university, Kerala, India
  • M Azath Head of Department, Department of computer Science, Calicut University

Keywords:

Haze, Polarization, Depth Map, Contrast Maximization, Dark Channel Prior, Independent Component Analysis, Anisotropic Diffusion

Abstract

Most of the computer applications use digital images. Digital image processing acts an important role in the analysis and interpretation of data, which is in the digital form. Images and videos of outdoor scenes are mainly affected by the bad weather conditions such as haze, fog, mist etc. It will result in poor visibility of the scene caused by the lack of quality. It will make awful impact on applications like object detection, tracking and surveillance system. One of the major challenges is the restoration of actual original image from the degraded image with at most accuracy. This survey aims to study about various existing methods such as polarization, dark channel prior, depth map based method etc. are used for dehazing.

References

http://en.wikipedia.org/wiki/Haze

R. T. Tan, “Visibility in bad weather from a single image,” in Proc. IEEE Conf. Comput.Vis. Pattern Recognit.,2008, pp.1-8.

K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 12, pp. 2341–2353, Dec. 2011.

R. Fattal, “Single image dehazing,” ACM Trans. Graph., vol. 27, no. 3,p. 72, Aug. 2008.

J. Tarel, N. Hauti, “Fast visibility restoration from a single color or gray level image”,Proceedings of IEEE Internation Conference on Computer Vision (ICCV), Kyoto, Japan:IEEE Computer Society,2009, pp. 2201-2208.

T. Treibitz and Y. Y. Schechner, “Polarization: Beneficial for visibility enhancement?” in Proceedings of IEEE Conference Computer Vision Pattern Recognition, 2009.

Narasimhan, Srinivasa G. and Shree K. Nayar, "Contrast restoration of weather degraded images", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no.6,pp. 713-724, 2003.

Cosmin Ancuti, and Codruta O. Ancuti,“Effective Contrast-Based Dehazing for Robust Image Matching” IEEE Geoscience And Remote Sensing Letters, Vol. 11, No. 11, Nov 2014.

Schechner, Yoav Y., Srinivasa G. Narasimhan and Shree K. Nayar, "Instant dehazing of images using polarization", The Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition ( CVPR), vol. 1, pp. I-325, 2001.

Nayar, Shree K. and Srinivasa G. Narasimhan, “Vision in bad weather ", Proceedings of the Seventh IEEE International Conference on Computer Vision, vol. 2, pp. 820-827, 1999.

Narasimhan, Srinivasa G. and Shree K. Nayar, " Interactive (de) weathering of an image Using physical models " , IEEE Workshop on Color and Photometric Methods in Computer Vision, vol. 6 , no. 6.4, p. 1., France, 2003.

Tripathi, and S. Mukhopadhyay, "Single image fog removal using anisotropic diffusion.”Image Processing, Vol. 6, no. 7, pp. 966-975, 2012.

http://www.ijcea.com/wpcontent/uploads/2014/06/RUCHIKA_SHARMA_et_al.pdf

Cosmin Ancuti, and Codruta O. Ancuti, “image dehazing by multi scale fusion” IEEE Geoscience And Remote Sensing Letters, Vol. 11, No. 11, Nov 2014.

Downloads

Published

2015-01-31

How to Cite

[1]
A. Thomas and M. Azath, “A Survey on Image and Video Dehazing”, Int. J. Comp. Sci. Eng., vol. 3, no. 1, pp. 21–23, Jan. 2015.

Issue

Vol. 3 No. 1 (2015): IJCSE January Edition

Section

Review Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.