Enhanced Single Image Dehazing Technique based on HSV Color Space

Authors

  • Mohammed Khalid Othman Technical College of Informatics, Sulaimani Polytechnic University, Sulaimani, Kurdistan Region, Iraq
  • Alan Anwer Abdulla Department of Information Technology, College of Commerce, University of Sulaimani, Sulaimani, Iraq, Department of Information Technology, University College of Goizha, Sulaimani, Iraq

DOI:

https://doi.org/10.21928/uhdjst.v6n2y2022.pp135-146

Keywords:

Dehazing, Atmospheric Scattering Model, Color Spaces, HSV, Haze

Abstract

The clarity of images degrades significantly due to the impact of weather conditions such as fog and haze. Persistent particles scatter light, attenuating reflected light from the scene, and the dispersed atmospheric light will mix with the light received by the camera affecting image contrast in both outdoor and indoor images. Conventionally, the atmospheric scattering model (ATSM) is a model often used to recover hazy images. In ATSM, two unknown factors/parameters must be estimated: Airlight and scene transmission. The accuracy of these estimations has a significant influence on the dehazed image quality. This paper focuses on the first parameter. It introduces a new technique for estimating the airlight based on the HSV color space. The HSV color space is utilized to identify the haziest opaque area in the image. Consequently, the amount of airlight in the selected area is calculated. To assess the effectiveness of the suggested approach, the well-known dataset, RESIDE SOTS, has been used that contains two parts; namely, SOTS-indoor and SOTS-outdoor. Each of dataset includes 500 images. Experimental findings show that the suggested approach outperforms the existing techniques in terms of peak signal-to-noise-ratio and structural similarity index`.

References

A. A. Abdulla and M. W. Ahmed. “An improved image quality algorithm for exemplar-based image inpainting”. Multimedia Tools and Applications, vol. 80, no. 9, pp. 13143-13156, 2021.

S. F. Salih and A. A. Abdulla. “An improved content based image retrieval technique by exploiting bi-layer concept”. UHD Journal of Science and Technology (UHDJST), vol. 5, no. 1, pp. 1-12, 2021.

J. Y. Kim, L. S. Kim and S. H. Hwang. “An advanced contrast enhancement using partially overlapped sub-block histogram equalization”. IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 4, pp. 475-484, 2001.

M. J. Seow and V. K. Asari. “Ratio rule and homomorphic filter for enhancement of digital colour image”. Neurocomputing, vol. 69, no. 7-9, pp. 954-958, 2006.

Z. Rahman, D. J. Jobson, and G. A. Woodell. “Retinex processing for automatic image enhancement”. Journal of Electronic Imaging, vol. 13, no. 1, pp. 100-110, 2004.

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

S. G. Narasimhan and S. K. Nayar. “Removing weather effects from monochrome images”. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition CVPR, vol. 2, p. 2, 2001.

E. Namer, S. Shwartz and Y. Y. Schechner. “Skyless polarimetric calibration and visibility enhancement”. Optics Express, vol. 17, no. 2, pp. 472-493, 2009.

F. Liu, L. Cao, X. Shao, P. Han and X. Bin. “Polarimetric dehazing utilizing spatial frequency segregation of images”. Applied Optics, vol. 54, no. 27, pp. 8116-8122, 2015.

S. G. Narasimhan and S. K. Nayar. “Interactive (de) weathering of an image using physical models”. In: IEEE Workshop on color and photometric Methods in computer Vision, vol. 6, no. 6.4, p. 1.

J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele and D. Lischinsk. “Deep photo: Model-based photograph enhancement and viewing.” ACM Transactions on Graphics, vol. 27, no. 5, pp. 1-10, 2008.

K. He, J. Sun and X. Tang. “Single image haze removal using dark channel prior”. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 12, pp. 2341-2353, 2010.

J. Long, Z. Shi and W. Tang. “Fast haze removal for a single remote sensing image using dark channel prior”. 2012 International Conference on Computer Vision in Remote Sensing, pp. 132-135, 2012.

G. Meng, Y. Wang, J. Duan, S. Xiang and C. Pan. “Efficient image dehazing with boundary constraint and contextual regularization”. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 617-624, 2013.

J. B. Wang, N. He, L. L. Zhang and K. Lu. “Single image dehazing with a physical model and dark channel prior”. Neurocomputing, vol. 149, pp. 718-728, 2015.

K. He, J. Sun and X. Tang. “Guided image filtering”. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 6, pp. 1397-1409, 2012.

A. Levin, D. Lischinski and Y. Weiss. “A closed-form solution to natural image matting”. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 2, pp. 228-242, 2007.

D. Berman and S. Avidan. “Non-local image dehazing”. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1674-1682, 2016.

R. J. Fattal. “Single image dehazing”. ACM Transactions on Graphics, vol. 27, no. 3, pp. 1-9, 2008.

J. P. Tarel and N. Hautiere. “Fast visibility restoration from a single color or gray level image”. In: 2009 IEEE 12th international conference on computer vision, pp. 2201-2208, 2009.

H. Lu, Y. Li, S. Nakashima and S. Serikawa. “Single image dehazing through improved atmospheric light estimation”. Multimedia Tools and Applications, vol. 75, no. 24, pp. 17081-17096, 2016.

S. Salazar-Colores, J. M. Ramos-Arreguín, J. C. Pedraza-Ortega and J. Rodríguez-Reséndiz. “Efficient single image dehazing by modifying the dark channel prior”. EURASIP Journal on Image and Video Processing, vol. 2019, no. 1, p.66, 2019.

C. Dai, M. Lin, X. Wu and D. Zhang. “Single hazy image restoration using robust atmospheric scattering model”. Signal Processing, vol. 166, p. 107257, 2020.

Y. Gao, Y. Zhang, H. Li and W. Zhang. “Single image dehazing based on single pixel energy minimization”. Multimedia Tools and Applications, vol. 80, no. 4, pp. 5111-5129, 2021.

L. Zhang, S. Wang and X. Wang. “Single image dehazing based on bright channel prior model and saliency analysis strategy”. IET Image Processing, vol. 15, no. 5, pp. 1023-1031, 2021.

Y. Yang and Z. Wang. “Haze removal: Push DCP at the edge”. IEEE Signal Processing Letters, vol. 27, pp. 1405-1409, 2020.

F. Sun, S. Wang, G. Zhao and M. Chen. “Single-image dehazing based on dark channel prior and fast weighted guided filtering”. Journal of Electronic Imaging, vol. 30, no. 2, p. 021005, 2021.

S. C. Raikwar, S. Tapaswi. “Estimation of minimum color channel using difference channel in single image Dehazing”. Multimedia Tools and Applications, vol. 80, no. 21, pp. 31837-31863, 2021.

S. Riaz, M. W. Anwar, I. Riaz, H. W. Kim, Y. Nam and M. A. Khan. “Multiscale image dehazing and restoration: An application for visual surveillance”. Computers, Materials and Continua, vol. 70, pp. 1-17, 2021.

E. J. McCartney. “Optics of the atmosphere: Scattering by molecules and particles”. Physics Bulletin, p. 421, 1976.

W. Wang, F. Chang, T. Ji and X. Wu. “A fast single-image dehazing method based on a physical model and gray projection”. IEEE Access, vol. 6, pp. 5641-5653, 2018.

Q. Zhu, J. Mai and L. Shao. “A fast single image haze removal algorithm using color attenuation prior”. IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 3522-3533, 2015.

B. Li, W. Ren, D. Fu, D. Tao, D. Feng, W. Zeng and Z. Wang. “Benchmarking single-image dehazing and beyond”. IEEE Transactions on Image Processing, vol. 28, no. 1, pp. 492-505, 2019.

Z. Wang, A. C. Bovik, H. R. Sheikh and E. Simoncelli. “Image quality assessment: From error visibility to structural similarity”. IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600- 612, 2004.

A. Hore and D. Ziou. “Image quality metrics: PSNR vs. SSIM”. In: 2010 20th International Conference on Pattern Recognition, pp. 2366-2369, 2010.

Published

2022-12-01

How to Cite

Othman, M. K., & Abdulla, A. A. (2022). Enhanced Single Image Dehazing Technique based on HSV Color Space. UHD Journal of Science and Technology, 6(2), 135–146. https://doi.org/10.21928/uhdjst.v6n2y2022.pp135-146

Issue

Section

Articles