CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Evaluating the Research Gaps of Underwater Image Enhancement Techniques

by Davinder Singh Baajwa, S.a.khan, Jaideep Kaur
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 20
Year of Publication: 2015
Authors: Davinder Singh Baajwa, S.a.khan, Jaideep Kaur
10.5120/20672-3369

Davinder Singh Baajwa, S.a.khan, Jaideep Kaur . Evaluating the Research Gaps of Underwater Image Enhancement Techniques. International Journal of Computer Applications. 117, 20 ( May 2015), 19-23. DOI=10.5120/20672-3369

@article{ 10.5120/20672-3369,
author = { Davinder Singh Baajwa, S.a.khan, Jaideep Kaur },
title = { Evaluating the Research Gaps of Underwater Image Enhancement Techniques },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 20 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 19-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number20/20672-3369/ },
doi = { 10.5120/20672-3369 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:59:56.598755+05:30
%A Davinder Singh Baajwa
%A S.a.khan
%A Jaideep Kaur
%T Evaluating the Research Gaps of Underwater Image Enhancement Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 20
%P 19-23
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Enhancement is among the challenging factors in image processing. The goal of enhancement is to enhance the structural appearance of a picture without the degradation in the input image. The enhancement techniques make the identification of key features easier by eliminating noise and other artifacts within an image. In this paper, we present an overview of image enhancement processing techniques applied on visibility restoration. More specifically, we categorize processing methods based on representative techniques of Image enhancement.

References
  1. Xu, Zhiyuan, Xiaoming Liu, and Na Ji. "Fog removal from color images using contrast limited adaptive histogram equalization. " In Image and Signal Processing, 2009. CISP'09. 2nd International Congress on, pp. 1-5. IEEE, 2009.
  2. Tripathi, A. K. , and S. Mukhopadhyay. "Single image fog removal using bilateral filter. " In Signal Processing, Computing and Control (ISPCC), 2012 IEEE International Conference on, pp. 1-6. IEEE, 2012.
  3. Wang, Yan, and Bo Wu. "Improved single image dehazing using dark channel prior. " Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on. Vol. 2. IEEE, 2010.
  4. M. Chambah, D. Semani, A. Renouf, P. Courtellemont, A. Rizzi, ``Underwater Color Constancy : Enhancement of Automatic Live Fish Recognition", 2003.
  5. Alan Weidemanna, Georges R. Fournierb, L. Forandb and P. Mathieub "aNaval Research Laboratory, Stennis Division, Stennis Space Center, Stennis , "In harbor underwater threat detection/identification using active imaging" 2003.
  6. Luz A. Torres-M´endez and Gregory Dudek, "Color Correction of Underwater Images for Aquatic Robot Inspection", 2005.
  7. St. Bazeille, Isabelle Quidu, Luc Jaulin, Jean-Phillipe Malkasse, "Automatic Underwater Image Pre-Processing", published in "CMM'06, Brest : France 2006.
  8. Kashif Iqbal, Rosalina Abdul salam, Azam osman and Abdullahzawawiralib, "Underwater Image Enhancement Usin g an Integrated Colour Model" , IAENG International Journal of computer science, vol 34, no. 2, Nov . 2007.
  9. Wang, Yan, and Bo Wu. "Improved single image dehazing using dark channel prior. " Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on. Vol. 2. IEEE, 2010.
  10. Shuai, Yanjuan, Rui Liu, and Wenzhang He. "Image Haze Removal of Wiener Filtering Based on Dark Channel Prior. " Computational Intelligence and Security (CIS), 2012 Eighth International Conference on. IEEE, 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Image Enhancement Visibility Restoration Haze Removal

Powered by PhDFocusTM