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Modified Haze Removal Algorithm for Image Using Color Attenuation Prior

Pavan Kumar Alanka*, Kiran Mounika Gedela**, Chinna Rao Chippada***, Srija Varma****, CH. Gayatri*****

*-***** Department of Electronics and Communication Engineering, Lendi institute of Engineering and Technology, Viziangaram, Andhra Pradesh, India.

Periodicity:July - September'2019
DOI : https://doi.org/10.26634/jip.6.3.16699

Abstract

Haze removal is a serious problem while dealing with single image. In this paper, the authors have proposed a new simple and powerful method to dehaze an image called color attenuation prior. Here, a depth map of the image has to be created at first, from a previously created linear model under the novel prior. From this find the transmission map so as to retrieve the depth information clearly. Then the last step is scene radiance recovery from which it is possible to get the dehazed image. The scene radiance recovery is done by the using the difference between saturation and the brightness of pixels. The experimental results show that the proposed method is very efficient and has a advantage, that it can dehaze sky images too.

Keywords

Dehazing, Defog, Image restoration, Depth restoration.

How to Cite this Article?

Alanka, P. K., Gedela, K. M., Chippada, C. R., Varma, S., and Gayatri, CH. (2019). Modified Haze Removal Algorithm for Image Using Color Attenuation Prior. i-manager's Journal on Image Processing, 6(3), 17-23. https://doi.org/10.26634/jip.6.3.16699

References

[1]. Fattal, R. (2008). Single image dehazing. ACM Transactions on Graphics (TOG), 27(3), 72. https://doi.org/ 10.1145/1399504.1360671

[2]. He, K., Sun, J., & Tang, X. (2011). Single image haze removal using dark channel prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(12), 2341- 2353. https://doi.org/10.1109/TPAMI.2010.168

[3]. McCartney, E. J. (1975). Optics of the Atmosphere: Scattering by Molecules and Particles. John Wiley and Sons.

[4]. Narasimhan, S. G., & Nayar, S. K. (2003). Contrast restoration of weather degraded images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(6), 713-724. https://doi.ieeecomputer society.org/10.1109/TPAMI.2003.1201821

[5]. Preetham, A. J., Shirley, P., & Smits, B. (1999). A practical analytic model for daylight. ACM Special Interest Group for Computer Graphics (SIGGRAPH), (pp. 91-100). https://doi.org/10.1145/311535. 311545

[6]. Schaul, L., Fredembach, C., & Süsstrunk, S. (2009, November). Color image dehazing using the near-infrared. In 2009 16^th IEEE International Conference on Image Processing (ICIP) (pp. 1629-1632). IEEE. https://doi.org/10.1109/ICIP.2009.5413700

[7]. Schechner, Y. Y., Narasimhan, S. G., & Nayar, S. K. (2001, December). Instant Dehazing of Images using Polarization. In Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (pp. 325-332). https://doi.org/10.1109/ CVPR.2001.990493

[8]. Tripathi, A. K., & Mukhopadhyay, S. (2012). Single image fog removal using anisotropic diffusion. IET Image Processing, 6(7), 966-975. https://doi.org/10.1049/ietipr. 2011.0472

[9]. Xu, Z., Liu, X., & Ji, N. (2009, October). Fog removal from color images using contrast limited adaptive histogram equalization. In 2009 2^nd International Congress on Image and Signal Processing (pp. 1-5), IEEE. https://doi.org/10.1109/CISP.2009.5301485

[10]. Zhu, Q., Mai, J., & Shao, L. (2015). A fast single image haze removal algorithm using color attenuation prior. IEEE Transactions on Image Processing, 24(11), 3522-3533. https://doi.org/10.1109/TIP.2015.2446191

Modified Haze Removal Algorithm for Image Using Color Attenuation Prior

Abstract

Keywords

How to Cite this Article?

References

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