Color correction of underwater images for aquatic robot inspection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3757 LNCS, Issue , 2005, Pages 60-73

  Torres Méndez, Luz A ^a   Dudek, Gregory ^a  

^a MCGILL UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ANALYSIS; MARKOV PROCESSES; REQUIREMENTS ENGINEERING; ROBOTICS; STATISTICAL METHODS; UNDERWATER IMAGING;

BELIEF PROPAGATION (BP); COLOR CORRECTION; MARKOV RANDOM FIELD (MRF); ROBOT INSPECTION;

COLOR IMAGE PROCESSING;

EID: 33646565008     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11585978_5     Document Type: Conference Paper

References (17)

1. J. Ȧhlén and D. Sundgren. Bottom reflectance influence on a color correction algorithm for underwater images. In Proc. SCIA, pages 922-926, 2003.
2. J. Besag. Spatial interaction and the statistical analysis of lattice systems (with discussion). J. Royal Statistics Society B, 36:192-326, 1974.
3. T. Boult. DOVE: Dolphin omni-directional video equipment. In Proc.Int. Conf. Robotics and Automation, pages 214-220, 2000.
4. J. Dera. Marine Physics. Elsevier, 1992.
5. R.C. Dubes, A.K. Jain, S.G. Nadabar, and C.C. Chen. Mrf model-based algorithms for image segmentation. In Proc. of IEEE Intl. Conf. on Pattern Recognition (ICPR), pages 808-814, 1990.
6. G.L. Foresti. Visual inspection of sea bottom structures by an autonomous underwater vehicle. IEEE Trans. Syst. Man and Cyber., Part B, 31:691-795, 2001.
7. W.T. Freeman, E.C. Pasztor, and O.T. Carmichael. Learning low-level vision. International Journal of Computer Vision, 20(1):25-47, 2000.
8. S. Geman and D. Geman. Stochastic relaxation, gibbs distributions, and the bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6:721-741, 1984.
9. C. Georgiades, A. German, A. Hogue, H. Liu, C. Prahacs, A. Ripsman, R. Sim, L. A. Torres-Méndez, P. Zhang, M. Buehler, G. Dudek, M. Jenkin, and E. Milios. AQUA: an aquatic walking robot. In Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, volume 3, pages 3525-3531, Sendai, Japan, September 2004. IEEE/RSJ, IEEE Press.
10. S. Harsdorf, R. Reuter, and S. Tonebon. Contrast-enhanced optical imaging of submersible targets. In Proc. SPIE, volume 3821, pages 378-383, 1999.
11. J.S. Jaffe. Computer modeling and the design of optimal underwater imaging systems. IEEE J. Oceanic Engineering, 15:101-111, 1990.
12. J. Pearl. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers, Inc., 1988.
13. C. Poynton. A Technical Introduction to Digital Video. Wiley, NewYork, 1996.
14. Y.Y. Schechner and N. Karpel. Clear underwater vision. In Proc. of Intt. Conference of Vision and Pattern Recognition, volume 1, pages 536-543, 2004.
15. Y. Weiss. Belief propagation and revision in networks with loops. Technical report, Berkeley Computer Science Dept., 1998.
16. G. Wyszecki and W.S. Stiles. Color Science: Concepts and Methods, Quantitative Data and Formulae. Wiley, NewYork, 1982.
17. J. Yedidia, W. Freeman, and Y. Weiss. Constructing free energy approximations and generalized belief propagation algorithms. Technical report, Mitsubishi Electrical Research Laboratories, Inc., 2004.