Abstract
This paper presents an algorithm for spots detection in Synthetic Aperture Radar (SAR) images that can be used to support environmental remote monitoring. Monitoring areas with high frequency of oil spillage by accidental or illegal oil discharges can prevent marine damage spreading. But the presence of speckle noise in SAR images limits the visual interpretation of scenes because it obscures the content. Thus, to get reliable data interpretation and quantitative spots measurements, it is recommended to applying speckle filtering schemes. We propose an algorithm to locate dark areas in the sea that are candidate to be oil slicks by combining region growing approach and multiscale analysis. The multiscale analysis employed by the undecimated wavelet smooths the speckle noise in SAR images while enhances edges. The proposed algorithm provides a better segmentation result that is achieved by a modified region growing approach. The algorithms were tested in real SAR images with oil spillages in the sea.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Marghany, M.: Radarsat Automatic Algorithms for Detecting Coastal Oil Spill Pollution. Asian Journal of Geoinformatics 3(2), 191–196 (2001)
Trivero, P., Fiscella, B., Gomez, F., Pavese, P.: SAR Detection and Characterization of Sea surface Slicks. Int. J. Remote Sensing 19, 543–548 (1988)
Stringer, W.J., Dean, K.G., Guritz, R.M., Garbeil, H.M., Groves, J.E., Ahlnaes, K.: Detection of Petroleum Spilled from the MV Exxon Valdez. Int. J. Remote Sensing 13(5), 799–824 (1992)
Solberg, A.H.S., Storvik, G., Solberg, R., Volden, E.: Automatic Detection of oil Spills in ERS SAR Images. IEEE Trans. on Geoscience and Remote Sensing 37(4), 1916–1924 (1999)
Liu, A.K., Peng, C.Y., Chang, S.Y.-S.: Wavelet Analysis of Satellite Image for Coastal Watch. IEEE Int. Journ. of Oceanic Engineering 22(1) (1997)
Del Frate, F.S., Petrocchi, A., Lichtenegger, J., Calabresi, G.: Neural Networks for Oil Spill Detection Using ERS-SAR Data. IEEE Trans. on Geoscience and Remote Sensing 38(5), 2282–2287 (2000)
Malladi, R., Sethian, J.A.: Image Processing via Level Set Curvature Flow. Proc. Natl. Acad. of Sci. 92(15), 7046–7050 (1995)
Mallat, S.G.: A Wavelet Tour of Signal Processing, 2nd edn. Academic Press, Cambrige (1998)
Starck, J.L., Murtagh, F., Bijaoui, A.: Image Processing and Data Analysis: The Muliscale Approach. Cambridge University Press, Cambridge (1998)
Medeiros, F.N.S., Mascarenhas, N.D.A., Marques, R.C.P., Laprano, C.M.: Edge Preserving Wavelet Speckle Filtering. In: Southwest Symposium on Image Analysis and Interpretation, Santa Fe, New Mexico, pp. 281–285 (2002)
Gonzalez, R.C., Woods, R.E.: Processamento de Imagens Digital. Edgard Blücher Ltda, São Paulo, Brazil (2000)
Sita, G., Ramakrishnan, A.G.: Wavelet Domain Nonlinear Filtering for Evoked Potential Signal Enhancement. Computers and Biomedical Research 33(6), 431–446 (2000)
Marques, R.C.P., Laprano, C.M., Medeiros, F.N.S.: Multiscale Denoising Algorithm Based on the à Trous Algorithm. In: Proceedings of SIBGRAPI 2002 - XV Brazilian Symposim on Computer Graphics and Image Processing, Fortaleza, Ceará, Brazil, p. 400 (2002)
Lombardo, P., Oliver, C.J.: Optimum Detection and Segmentation of Oil-Slicks with Polarimetric SAR Data. In: IEEE International Radar Conference, pp. 122–127 (2000)
Glasbey, C.A., Horgan, G.W.: Image analysis for the biologic sciences. John Wiley & Sons, Chichester (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Araújo, R.T.S., de Medeiros, F.N.S., Costa, R.C.S., Marques, R.C.P., Moreira, R.B., Silva, J.L. (2004). Locating Oil Spill in SAR Images Using Wavelets and Region Growing. In: Orchard, B., Yang, C., Ali, M. (eds) Innovations in Applied Artificial Intelligence. IEA/AIE 2004. Lecture Notes in Computer Science(), vol 3029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24677-0_121
Download citation
DOI: https://doi.org/10.1007/978-3-540-24677-0_121
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22007-7
Online ISBN: 978-3-540-24677-0
eBook Packages: Springer Book Archive