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Reseach Article

Result Analysis-Edge-Preserving Decomposition-based Single Image Haze Removal

by Puja Rani Boipai, Sonulal, Deepak Mishra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 158 - Number 10
Year of Publication: 2017
Authors: Puja Rani Boipai, Sonulal, Deepak Mishra
10.5120/ijca2017912860

Puja Rani Boipai, Sonulal, Deepak Mishra . Result Analysis-Edge-Preserving Decomposition-based Single Image Haze Removal. International Journal of Computer Applications. 158, 10 ( Jan 2017), 25-28. DOI=10.5120/ijca2017912860

@article{ 10.5120/ijca2017912860,
author = { Puja Rani Boipai, Sonulal, Deepak Mishra },
title = { Result Analysis-Edge-Preserving Decomposition-based Single Image Haze Removal },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 158 },
number = { 10 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 25-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume158/number10/26944-2017912860/ },
doi = { 10.5120/ijca2017912860 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:04:27.645321+05:30
%A Puja Rani Boipai
%A Sonulal
%A Deepak Mishra
%T Result Analysis-Edge-Preserving Decomposition-based Single Image Haze Removal
%J International Journal of Computer Applications
%@ 0975-8887
%V 158
%N 10
%P 25-28
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the increase in industrial production and human activities, the concentration of atmospheric particulate matter (PM) is substantial increased, leading to fog and haze occurs more frequently. Limited visibility caused by suspended particles in the air, such as fog and haze, is a major problem for many applications of computer vision. The captured scenes by such computer vision systems suffer from poor visibility, low contrast, dimmed brightness, low luminance and distorted color, which makes detection of objects within the scene more difficult. Therefore visibility improvement, contrast and features enhancement of images and videos captured in bad weather, also called as dehazing, and is an inevitable task. Furthermore, estimated actual weather condition is valuable information to invoke corresponding approaches.

References
  1. Zhengguo Li, and Jinghong Zheng, “Edge-Preserving Decomposition-Based Single Image Haze Removal”, Ieee Transactions On Image Processing, Vol. 24, No. 12, December 2015
  2. Yuan-Kai Wang and Ching-Tang Fan “Single Image Defogging by Multiscale Depth Fusion”, IEEE Transactions On Image Processing, Vol. X, No. X, Month 2014.
  3. Faming Fang, Fang Li, and Tieyong Zeng “Single Image Dehazing and Denoising: A Fast Variational Approach”, 2014 Society for Industrial and Applied Mathematics.
  4. Codruta Orniana Ancuti and Cosmin Ancuti “Single Image Dehazing by Multi-Scale Fusion”. IEEE Transactions On Image Processing, Vol. 22, No. 8, August 2013.
  5. Jing Yu, Qingmin Liao “Fast Single Image Fog Removal Using Edge-Preserving Smoothing”, 978-1-4577-0539-7/11/$26.00 ©2011 IEEE
  6. Raanan Fatta “Single Image Dehazing”, Hebrew University of Jerusalem, Israel.
  7. S. G. Narasimhan and S. K. Nayar, “Chromatic framework for vision in bad weather,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Hilton Head Island, SC, USA, Jun. 2000, pp. 598–605.
  8. S. G. Narasimhan and S. K. Nayar, “Contrast restoration of weather degraded images,” IEEE Trans. Pattern Anal. Mach. Learn., vol. 25, no. 6, pp. 713–724, Jun. 2003.
  9. J. Kopf et al., “Deep photo: Model-based photograph enhancement and viewing,” ACM Trans. Graph., vol. 27, no. 5, pp. 1–10, May 2008.
  10. 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.
  11. X. Y. Lv, W. Chen, and I. Shen, “Real-time dehazing for image and video,” in Proc. 18th Pacific Conf. Comput. Graph. Appl., Hangzhou, China, Sep. 2010, pp. 62–69.
  12. J. Pang, O. C. Au, and Z. Guo, “Improved single image dehazing using guided filter,” in Proc. APSIPA ASC, Xi’an, China, 2011, pp. 1–4.
  13. K. He, J. Sun, and X. Tang, “Guided image filtering,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 6, pp. 1397–1409, Jun. 2013.
  14. Z. Li, J. Zheng, Z. Zhu, W. Yao, and S. Wu, “Weighted guided image filtering,” IEEE Trans. Image Process., vol. 24, no. 1, pp. 120–129, Jan. 2015.
Index Terms

Computer Science
Information Sciences

Keywords

Single image haze removal edge-preserving smoothing weighted guided image filtering minimal color channel.