CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Improved Haze Removal of Underwater Images using Particle Swarm Optimization

by Shriya Sharma, Sakshi Bhalla
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 4
Year of Publication: 2015
Authors: Shriya Sharma, Sakshi Bhalla
10.5120/21687-4792

Shriya Sharma, Sakshi Bhalla . Improved Haze Removal of Underwater Images using Particle Swarm Optimization. International Journal of Computer Applications. 122, 4 ( July 2015), 12-18. DOI=10.5120/21687-4792

@article{ 10.5120/21687-4792,
author = { Shriya Sharma, Sakshi Bhalla },
title = { Improved Haze Removal of Underwater Images using Particle Swarm Optimization },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 4 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 12-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number4/21687-4792/ },
doi = { 10.5120/21687-4792 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:09:41.259853+05:30
%A Shriya Sharma
%A Sakshi Bhalla
%T Improved Haze Removal of Underwater Images using Particle Swarm Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 4
%P 12-18
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The main objective of fog removal algorithm is to estimate the airlight map for the given image and then perform the necessary operations on the image in order to overcome the fog in the image and enhance the quality of the image. The dark channel prior method of fog removal is more suitable and time-saving in real-time systems. In this paper, an efficient approach for fog removal of foggy images based on the combination of dark channel prior and genetic algorithm is presented. It is found that the proposed method is more suitable for obtaining the better quality of the image than the most of the existing methods.

References
  1. Podzimek, Josef. "Aerosol particle scavenging by fog and haze droplets. "Studia Geophysica et Geodaetica 42, no. 4 (1998): 540-560.
  2. Chu, Chao-Tsung, and Ming-Sui Lee. "A content-adaptive method for single image dehazing. " In Advances in Multimedia Information Processing-PCM 2010, pp. 350-361. Springer Berlin Heidelberg, 2010.
  3. Ancuti, Codruta O. , Cosmin Ancuti, Chris Hermans, and Philippe Bekaert. "A fast semi-inverse approach to detect and remove the haze from a single image. " In Computer Vision–ACCV 2010, pp. 501-514. Springer Berlin Heidelberg, 2011.
  4. Zhang, Yong-Qin, Yu Ding, Jin-Sheng Xiao, Jiaying Liu, and Zongming Guo. "Visibility enhancement using an image filtering approach. " EURASIP Journal on Advances in Signal Processing 2012, no. 1 (2012): 1-6.
  5. Xiao, Chunxia, and Jiajia Gan. "Fast image dehazing using guided joint bilateral filter. " The Visual Computer 28, no. 6-8 (2012): 713-721.
  6. Xie, Bin, Fan Guo, and Zixing Cai. "Fast Haze Removal Algorithm for Surveillance Video. " In Measuring Technology and Mechatronics Automation in Electrical Engineering, pp. 235-241. Springer New York, 2012.
  7. Kim, Eun-Kyoung, Jae-Dong Lee, Byungin Moon, and Yong-Hwan Lee. "Hardware Architecture of Bilateral Filter to Remove Haze. " In Communication and Networking, pp. 129-135. Springer Berlin Heidelberg, 2012.
  8. Ding, Meng, and RuoFeng Tong. "Efficient dark channel based image dehazing using quadtrees. " Science China Information Sciences 56, no. 9 (2013): 1-9.
  9. Xue, Yungang, Ju Ren, Huayou Su, Mei Wen, and Chunyuan Zhang. "Parallel Implementation and Optimization of Haze Removal Using Dark Channel Prior Based on CUDA. " In High Performance Computing, pp. 99-109. Springer Berlin Heidelberg, 2013.
  10. Lan, Xia, Liangpei Zhang, Huanfeng Shen, Qiangqiang Yuan, and Huifang Li. "Single image haze removal considering sensor blur and noise. " EURASIP Journal on Advances in Signal Processing 2013, no. 1 (2013): 1-13.
  11. Ogorodnikov, B. I. , and V. E. Khan. "Impact of haze and fog on filter characteristics in the process of monitoring radioactive aerosol. " Russian Meteorology and Hydrology 38, no. 11 (2013): 787-791.
  12. Guo, Fan, Jin Tang, and Zi-Xing Cai. "Image dehazing based on haziness analysis. " International Journal of Automation and Computing 11, no. 1 (2014): 78-86.
  13. Galdran, Adrian, Javier Vazquez-Corral, David Pardo, and Marcelo Bertalmío. "A Variational Framework for Single Image Dehazing. " In Computer Vision-ECCV 2014 Workshops, pp. 259-270. Springer International Publishing, 2014.
  14. Zhang, Jun, and Shiqiang Hu. "A GPU-accelerated real-time single image de-hazing method using pixel-level optimal de-hazing criterion. " Journal of Real-Time Image Processing 9, no. 4 (2014): 661-672.
  15. Liu, Qian, MaoYin Chen, and DongHua Zhou. "Single image haze removal via depth-based contrast stretching transform. " Science China Information Sciences: 1-17. Volume 58, Issue 1, pp 1-17, 2014
  16. Gadnayak, Khitish Kumar, Pankajini Panda, and Niranjan Panda. "Haze Removal: An Approach Based on Saturation Component. " In Intelligent Computing, Communication and Devices, pp. 281-287. Springer India, 2015.
  17. Fan, Xin, Yi Wang, Renjie Gao, and Zhongxuan Luo. "Haze editing with natural transmission. " The Visual Computer (2015): 1-11.
  18. Ling, Zhigang, Shutao Li, Yaonan Wang, He Shen, and Xiao Lu. "Adaptive transmission compensation via human visual system for efficient single image dehazing. " The Visual Computer (2015): 1-10.
Index Terms

Computer Science
Information Sciences

Keywords

Dark Channel Prior Genetic Algorithm Transmission Map

Powered by PhDFocusTM