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Detection of Fronts from Ocean Colour Monitor Images Using Entropic Technique: A Case Study of Meso- and Micro-Scale Chlorophyll Mapping in Bay of Bengal, India

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DOI: 10.4236/ars.2013.22010    3,939 Downloads   6,332 Views   Citations

ABSTRACT

This paper discusses a robust technique using entropy-based detection for delineating edges in ocean colour images. The detection process relies on Jhensen-Shannon divergence based image segmentation, which has been found to be the most suitable for noisy ocean colour images. In the attempted technique, partial removal of the noise in the images is performed and the edges are detected using entropic method. In our approach, Jhensen-Shannon divergence for the images is calculated, and the divergence image is arrived at after applying an appropriate threshold and filter to estimate the gradients. An attempted case study on retrieving chlorophyll front edges using this technique indicates that entropic method is far superior to conventional edge-enhancement tools, in terms of its insensitivity to impulsive noises and, capability in detecting meso- and micro-scale changes. This procedure would largely decrease the ambiguities associated with the ocean colour edges and hence has promising application potential in targeting fishing zones, sediment dispersion modeling and climate related studies.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

R. Vinuchandran and D. Ramakrishnan, "Detection of Fronts from Ocean Colour Monitor Images Using Entropic Technique: A Case Study of Meso- and Micro-Scale Chlorophyll Mapping in Bay of Bengal, India," Advances in Remote Sensing, Vol. 2 No. 2, 2013, pp. 71-76. doi: 10.4236/ars.2013.22010.

References

[1] C. R. Savage, R. J. Petrell and T. P. Neyfeld, “Underwater Fish Video Images: Image Quality and Edge Detection Techniques,” Canadian Agricultural Engineering, Vol. 36, No. 3, 1994, pp. 175-183.
[2] D. Sauter and L. Parson, “Spatial Filtering for Speckle Reduction Contrast Enhancement, and Texture Analysis of GLORIA Images,” IEEE Journal of Oceanic Engineering, Vol. 19, No. 4, 1994, pp. 563-576. doi:10.1109/48.338392
[3] M. F. Janowitz, “Automatic Detection of Gulf Stream Rings,” Office of Naval Research Technical Report, Massachusetts University, Amherst, 1985.
[4] T. Shimada, F. Sakaida, H. Kawamura and T. Okumura, “Application of an Edge Detection Method to Satellite Images for Distinguishing Sea Surface Temperature Fronts Near the Japanese Coast,” Remote Sensing of Environment, Vol. 98, No. 1, 2005, pp. 21-34. doi:10.1016/j.rse.2005.05.018
[5] S. Mallat and S. Zhong, “Characterization of Signals from Multiscale Edges,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14, No. 7, 1992, pp. 701-732. doi:10.1109/34.142909
[6] F. Song and S. Jutamulia, “New Wavelet Transforms for Noise-Insensitive Edge Detection,” Optical Engineering, Vol. 41, No. 1, 2002, pp. 50-54. doi:10.1117/1.1424877
[7] C.-P. Huang and R.-Z. Wang, “An Integrated Edge Detection Method Using Mathematical Morphology,” Pattern Recognition and Image Analysis, Vol. 16, No. 3, 2006, pp. 406-412. doi:10.1134/S1054661806030102
[8] D. P. Vazques and C. Atae-Allah, “Entropic Approach to Edge Detection for SST Images,” Journal of Atmospheric and Oceanic Technology, Vol. 16, No. 7, 1998, pp. 970-979. doi:10.1175/1520-0426(1999)016<0970:EATEDF>2.0.CO;2
[9] M. Mohan, P. Chauhan, A. Mathur and R. M. Dwivedi, “Atmospheric Correction of MOS-B Data Using Long Wavelength and PCI Based Approaches, IRS-P3 MOS Validation Experiment: Ocean Applications,” Space Application Centre, Ahmedabad, 1998, pp. 14-22.
[10] P. Chauhan, M. Mohan, R. K. Sarangi, B. Kumari and S. Nayak, “Surface Chlorophyll-a Estimation in the Bay of Bengal Using IRS-P4 Ocean Colour Monitor (OCM) Satellite Data,” International Journal of Remote Sensing, Vol. 23, No. 8, 2002, pp. 1663-1676. doi:10.1080/01431160110075866
[11] P. Cipollini, G. Corsini, M. Diani and R. Grasso, “Retrieval of Sea Water Optically Active Parameters from Hyperspectral Data by Means of Generalized Radial Basis Function Neural Networks,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 39, No. 7, 2001, pp. 1508-1524. doi:10.1109/36.934081
[12] J. E. O’Reilly, S. Maritorena, B. G. Mitchell, D. A. Scigal, K. L. Carder, S. A. Graver, M. Kahru and C. R. McClain, “Ocean Colour Chlorophyll Algorithms for SeaWiFS,” Journal of Geophysical Research, Vol. 103, No. C11, 1998, pp. 24937-24953.
[13] J. Lin, “Divergence Measures Based on the Shannon Entropy,” IEEE Transactions on Information Theory, Vol. 37, No. 1, 1991, pp. 145-150. doi:10.1109/18.61115
[14] L. V. Barranco, P. E. Luque, J. A. Martinea and R. R. Roldan, “Entropic Texture-Edge Detection for Image Segmentation,” Electronics Letters, Vol. 31, No. 1, 1995, pp. 867-869. doi:10.1049/el:19950598
[15] B. Singh and A. P. Singh, “Edge Detection in Grey Level Images Based on the Shanon Entropy,” Journal of Computer Science, Vol. 4, No. 3, 2008, pp. 186-191. doi:10.3844/jcssp.2008.186.191
[16] M. A. El-Sayed and T. A. Hafeez, “New Edge Detection Technique Based on the Shannon Entropy in Grey Level Images,” International Journal on Computer Science and Engineering, Vol. 3, No. 6, 2011, pp. 2224-2232.
[17] V. B. Lopez, P. L. Escamilla, J. M. Aroza and R. R. Roldan, “Entropic Texture-Edge Detection for Image Segmentation,” IEEE Electronic Letters, Vol. 31, No. 11, 1995, pp. 867-869. doi:10.1049/el:19950598
[18] J. F. Gomez-Lopera, J. M. Aeoza and A. M. Perez, “An Analysis of Edge Detection by Using the Jensen-Shannon Divergence,” Journal of Mathematical Imaging and Vision, Vol. 13, No. 1, 2000, pp. 35-56. doi:10.1023/A:1008325607354
[19] M. Wang and S. Y. Yuan, “A Hybrid Genetic Algorithm based Edge Detection Method for SAR Image,” IEEE Proceedings of the Radar Conference, Arlington, 9-12 May 2005, pp. 503-506.
[20] A. E. Hassanien, “Fuzzy Rough Sets Hybrid Scheme for Breast Cancer Detection,” Image and Vision Computing, Vol. 25, No. 2, 2007, pp. 172-183. doi:10.1016/j.imavis.2006.01.026
[21] R. Zhang, G. Zhao and S. Li, “A New Edge Detection Method in Image Processing,” IEEE Proceedings of the Communications and Information Technology, Arlington, 12-14 October 2005, pp. 445-448.

  
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