Open Access   Article Go Back

Underwater Image Restoration Based on Illumination Normalization and Deblurring

I. Jeya Kumar1 , A. Lenin Fred2 , C. Seldev Christopher3

  1. Department of CSE, Ponjesly College of Engineering, Nagercoil, India.
  2. Department of CSE, Mar Ephraem College of Engineering & Technology, Marthandam, India.
  3. Department of CSE, St.Xavier’s Catholic College of Engineering, Nagercoil, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-5 , Page no. 288-296, May-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i5.288296

Online published on May 31, 2018

Copyright © I. Jeya Kumar, A. Lenin Fred, C. Seldev Christopher . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: I. Jeya Kumar, A. Lenin Fred, C. Seldev Christopher, “Underwater Image Restoration Based on Illumination Normalization and Deblurring,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.288-296, 2018.

MLA Style Citation: I. Jeya Kumar, A. Lenin Fred, C. Seldev Christopher "Underwater Image Restoration Based on Illumination Normalization and Deblurring." International Journal of Computer Sciences and Engineering 6.5 (2018): 288-296.

APA Style Citation: I. Jeya Kumar, A. Lenin Fred, C. Seldev Christopher, (2018). Underwater Image Restoration Based on Illumination Normalization and Deblurring. International Journal of Computer Sciences and Engineering, 6(5), 288-296.

BibTex Style Citation:
@article{Kumar_2018,
author = {I. Jeya Kumar, A. Lenin Fred, C. Seldev Christopher},
title = {Underwater Image Restoration Based on Illumination Normalization and Deblurring},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {6},
Issue = {5},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {288-296},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1975},
doi = {https://doi.org/10.26438/ijcse/v6i5.288296}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i5.288296}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1975
TI - Underwater Image Restoration Based on Illumination Normalization and Deblurring
T2 - International Journal of Computer Sciences and Engineering
AU - I. Jeya Kumar, A. Lenin Fred, C. Seldev Christopher
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 288-296
IS - 5
VL - 6
SN - 2347-2693
ER -

VIEWS PDF XML
617 406 downloads 279 downloads
  
  
           

Abstract

The fundamental reason for submerged image handling is to enhance submerged image enhancement. The preparing of submerged image caught is essential in light of the fact that the nature of submerged images influence and these images drives some significant issues when contrasted with images from a clearer domain. Because of the presence of clean particles in the water, submerged images suffer from the backscattering impact. To overcome this drawback I propose the new method called illumination normalization and deblurring of underwater image restoration. In this paper propose, first estimate the illumination directions of underwater images and cope with the problem of illumination normalization. Secondly deblurring of the underwater image using deconvolution algorithm and finally by the fusing both the results the restored image is acquired.The quality of the enhanced image is evaluated by using the metric is called blind/reference less image spatial quality evaluator (BRISQUE).

Key-Words / Index Term

Image Restoration, Illumination Direction, Illumination Normalization, Deblurring, Deconvolution

References

[1] Bidyut Saha, “A Comparative Analysis of Histogram Equalization Based Image Enhancement Technique for Brightness Preservation”, International Journal of Scientific Research in Computer Science and Engineering, Vol.3, Issue.3, pp.1-5, 2015.
[2] Hussam Elbehiery, “Optical Fiber Cables Networks Defects Detection using Thermal Images Enhancement Techniques”, International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.1, pp.22- 29, 2018.
[3] J. Chiang, Y. Chen, “Underwater Image Enhancement by Wavelength Compensation and Dehazing,” IEEE Transaction on Image Processing, vol. 21, Issue.4, pp. 1756–1769, 2012.
[4] K. He., J. Sun, X. Tang, "Single Image Haze Removal Using Dark Channel Prior, "IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, Issue. 12, pp. 2341-2353, 2011.
[5] Adrian Galdran, David Pardo, ArtzaiPicón, and Aitor Alvarez-Gila, “Automatic Red-Channel underwater image restoration”, Science Direct, J. Vis. Commun. Image R. 26132–145, 2015.
[6] H. Wen, Y.Tian, T. Huang, W. Gao, “Single underwater image enhancement with a new optical model,” Proc. IEEE Int. Symp. Circ. & Syst. (ISCAS), pp. 753-756, 2013.
[7] Xinwei Zhao, Tao Jin, Song Qu, “Deriving inherent optical properties from background color and underwater image enhancement”, Lists available at Science Direct, Ocean Engineering 94163–172, 2015.
[8] R. Sathya, M. Bharathi, G. Dhivyasri, “Underwater Image Enhancement by Dark Channel Prior”, IEEE sponsored 2nd International Conference on Electronics and Communication System (ICECS), 2015.
[9] C.Y. Cheng, C.C. Sung, H.H. Chang, "Underwater image restoration by red-dark channel prior and point spread function deconvolution," IEEE International Conference on Signal and Image Processing Applications (ICSIPA), Kuala Lumpur, pp. 110-115, 2015.
[10] C. Ancuti, C.O. Ancuti, T. Haber, P. Bekaert, "Enhancing underwater images and videos by fusion, " IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, pp. 81- 88, 2012.
[11] N. Carlevaris-Bianco, A. Mohan, R.M. Eustice, “Initial results in underwater single image dehazing”, Proc. IEEE Oceans, pp. 1-8, 2010.
[12] HuiminLu, Seiichi Serikawa, “Underwater Scene Enhancement Using Weighted Guided Median Filter”, Marine Technology Society Journal, vol.42, Issue.1, pp.52-67, 2014.
[13] Yan-TsungPeng, Xiangyun Zhao, Pamela C. Cosman, “Single Underwater Image Enhancement Using Depth Estimation based on Blurriness”, IEEE International Conference on Image Processing (ICIP), pp.4952- 4956, 2015.
[14] X. Fu, P. Zhuang, Y. Huang, Y. Liao, X.P. Zhang, X. Ding, “A retinex-based enhancing approach for single underwater image”, in: IEEE Int. Conf. Image Process (ICIP), pp. 4572–4576, 2014.
[15] K. Seemakurthy, A.N. Rajagopalan, "Deskewing of Underwater Images, "IEEE Transactions on Image Processing, vol. 24, no. 3, pp.1046- 1059, 2015.
[16] Q. Zhu, J. Mai, L. Shao, "A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior, "IEEE Transactions on Image Processing, vol. 24, Issue. 11, pp. 3522-3533, 2015.
[17] Lei Fei and Wang Yingying, “The Research of Underwater Image De- noising Method Based on Adaptive Wavelet Transform”, IEEE Conference,pp.2521-2525, 2014.