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Reseach Article

Improved Air Light Estimation Algorithm by using Fuzzy Filters and Dark Channel with Large Haze Gradients

by Anil Rai, Harpreet K. Bajaj
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 166 - Number 4
Year of Publication: 2017
Authors: Anil Rai, Harpreet K. Bajaj
10.5120/ijca2017913989

Anil Rai, Harpreet K. Bajaj . Improved Air Light Estimation Algorithm by using Fuzzy Filters and Dark Channel with Large Haze Gradients. International Journal of Computer Applications. 166, 4 ( May 2017), 6-12. DOI=10.5120/ijca2017913989

@article{ 10.5120/ijca2017913989,
author = { Anil Rai, Harpreet K. Bajaj },
title = { Improved Air Light Estimation Algorithm by using Fuzzy Filters and Dark Channel with Large Haze Gradients },
journal = { International Journal of Computer Applications },
issue_date = { May 2017 },
volume = { 166 },
number = { 4 },
month = { May },
year = { 2017 },
issn = { 0975-8887 },
pages = { 6-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume166/number4/27655-2017913989/ },
doi = { 10.5120/ijca2017913989 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:12:46.918670+05:30
%A Anil Rai
%A Harpreet K. Bajaj
%T Improved Air Light Estimation Algorithm by using Fuzzy Filters and Dark Channel with Large Haze Gradients
%J International Journal of Computer Applications
%@ 0975-8887
%V 166
%N 4
%P 6-12
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Fog phenomena bring about air flow gentle generating and also decline this awareness involving made from photograph caught in the camera. To increase awareness, air flow gentle evaluation is essential regarding photograph errors removal. As air flow gentle can be quite dazzling, this conventional methods immediately select dazzling p regarding air flow gentle estimation.In this paper improved/hybrid fuzzy filters based haze removal algorithm is proposed. The dark channel prior can automatically extract the global atmospheric light and roughly eliminate the atmospheric veil. To make dark channel prior more effective, the atmospheric veil has been refined by using hybrid fuzzy filters as well as it able to produce a haze free image in more optimistic manner. The use of improved/hybrid fuzzy filters has improved the coarse estimated atmospheric veil by reducing halo artifacts.

References
  1. Atta, Randa, and Rabab Farouk Abdel-Kader. "Brightness preserving based on singular value decomposition for image contrast enhancement." Optik-International Journal for Light and Electron Optics 126, no. 7 (2015): 799-803.
  2. Bhandari, A. K., Anil Kumar, G. K. Singh, and Vivek Soni. "Dark satellite image enhancement using knee transfer function and gamma correction based on DWT–SVD." Multidimensional Systems and Signal Processing (2015): 1-24.
  3. Pathak SS, Dahiwale P, Padole G. A combined effect of local and global method for contrast image enhancement. In Engineering and Technology (ICETECH), 2015 IEEE International Conference on 2015 Mar 20 (pp. 1-5). IEEE.
  4. Ghosh, Soham, Sourya Roy, Utkarsh Kumar, and Arijit Mallick. "Gray Level Image Enhancement Using Cuckoo Search Algorithm." In Advances in Signal Processing and Intelligent Recognition Systems, pp. 275-286. Springer International Publishing, 2014.
  5. Ji X, Cheng J, Bai J, Zhang T, Wang M. Real-time enhancement of the image clarity for traffic video monitoring systems in haze. In Image and Signal Processing (CISP), 2014 7th International Congress on 2014 Oct 14 (pp. 11-15). IEEE
  6. Agarwal TK, Tiwari M, Lamba SS. Modified histogram based contrast enhancement using homomorphic filtering for medical images. In Advance Computing Conference (IACC), 2014 IEEE International 2014 Feb 21 (pp. 964-968). IEEE.
  7. Negi SS, Bhandari YS. A hybrid approach to Image Enhancement using Contrast Stretching on Image Sharpening and the analysis of various cases arising using histogram. In Recent Advances and Innovations
  8. Bouaziz A, Draa A, Chikhi S. A Cuckoo search algorithm for fingerprint image contrast enhancement. In Complex Systems (WCCS), 2014 Second World Conference on 2014 Nov 10 (pp. 678-685). IEEE.
  9. Mathew, Ammu Anna, and S. Kamatchi. "Brightness and Resolution Enhancement of Satellite Images using SVD and DWT." International Journal of Engineering Trends and Technology 4, no. 4 (2013): 712-718.
  10. Gupta, Nidhi, and Rajib Jha. "Enhancement of High Dynamic Range Dark Images Using Internal Noise in DWT Domain." In Intelligent Interactive Technologies and Multimedia, pp. 66-74. Springer Berlin Heidelberg, 2013.
  11. Huang, Shih-Chia and Chien-Hui Yeh. "Image contrast enhancement for preserving mean brightness without losing image features." Engineering Applications of Artificial Intelligence 26, no. 5 (2013): 148
  12. Xie, Zhihua. "Single sample face recognition based on dct and local Gabor binary pattern histogram." In Intelligent Computing Theories, pp. 435-442. Springer Berlin Heidelberg, 2013.
  13. Lee, Edward, Sungho Kim, Wei Kang, Daeban Seo, and Jamie Paik. "Contrast enhancement using dominant brightness level analysis and adaptive intensity transformation for remote sensing images." Geoscience and Remote Sensing Letters, IEEE 10, no. 1 (2013): 62-66.
  14. Wen, Haocheng, Yonghong Tian, Tiejun Huang, and Wen Gao "Single underwater image enhancement with a new optical model." In Circuits and Systems (ISCAS), 2013 IEEE International Symposium on, pp. 753-756. IEEE, 2013.
  15. Nercessian SC, Panetta K, Agaian SS. Non-linear direct multi-scale image enhancement based on the luminance and contrast masking characteristics of the human visual system. Image Processing, IEEE Transactions on. 2013 Sep; 22(9):3549-61.
  16. Huynh-The T, Le-Tien T. Brightness preserving weighted dynamic range histogram equalization for image contrast enhancement. In Advanced Technologies for Communications (ATC), 2013 International Conference on 2013 Oct 16 (pp. 386-391). IEEE.
  17. Kotkar VA, Gharde SS. Image contrast enhancement by preserving brightness using global and local features. In Computational Intelligence and Information Technology, 2013. CIIT 2013. Third International Conference on 2013 Oct 18 (pp. 262-271). IET.
  18. Bhandari AK, Gadde M, Kumar A, Singh GK. Comparative analysis of different wavelet filters for low contrast and brightness enhancement of multispectral remote sensing images. In Machine Vision and Image Processing (MVIP), 2012 International Conference on 2012 Dec 14 (pp. 81-86). IEEE.
  19. Gupta, Kanika, and Akshu Gupta. "Image enhancement using ant colony optimization." IOSR J. VLSI Signal Process 1 (2012): 38.
  20. Khan, Nafis Uddin, K. V. Arya, and Manisha Pattanaik. "A New Adaptive Thresholding in SVD for Efficient Image De-noising." In Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011, pp. 659-670. Springer India, 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Image defogging Dark channel prior Air light Estimation Fuzzy filtering.