Summary
This paper deals with the problem of detail-preserving processing of remotely sensed images. It describes two approaches based, on the use of the local adaptivity properties exploited by methods of the contextual type (for instance, the Markov Random Field model [6]) and on the application of fuzzy topology by the so-called isocontour method [2], respectively.
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.
References
J.C. Bezdek, Pattern recognition with fuzzy objective function algorithms, Plenum Press, New York, 1981.
S. Dellepiane, F. Fontana, and G. Vernazza, “Non-linear image labelling for multivalued segmentation”, IEEE Transactions on Image Processing, vol. 5, no. 3, pp. 429–446, 1996.
S. Dellepiane and F. Fontana, “Supervised fuzzy contextual segmentation of polarimetric SAR images”, European Transactions on Telecommunications, vol. 6, pp. 515–525, 1996.
R. 0. Duda and P.E. Hart, Pattern classification and Scene Analysis, Wiley Interscience, New York, 1974.
A. Freeman, J. Villasenor, J.D. Klein, P. Hoogeboom and J. Groot, “On the use of multi-frequency and polarimetric radar backscatter features for classification of agricultural crops”, International Journal of Remote Sensing, vol. 15, no. 9, pp. 1799–1812, 1994.
S. Geman and D. Geman, “Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 6, no. 6, pp. 721–741, 1984.
S.Z. Li, “On discontinuity-adaptive smoothness priors in computer vision”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, no. 6, pp. 576–586, 1995.
S.K. Pal and A. Rosenfeld, “Image enhancement and thresholding by optimization of fuzzy compactness”, Pattern Recognition Letters, vol. 8, pp. 21–28, 1988.
S.K. Pal and A. Ghosh, “Index of area coverage of fuzzy image subsets and object extraction”, Pattern Recognition Letters, vol. 11, pp. 831–841, 1990.
P. Perez and F. Heitz, “Restriction of a Markov random field on a graph and multiresolution statistical image modeling”, IEEE Transactions on Information Theory, vol. 42, no. 1, pp. 180–190, 1996.
E. Rignot and R. Chellappa, “Segmentation of polarimetric synthetic aperture radar data”, IEEE Transactions on Image Processing, vol. 1, no. 3, pp. 281–300, 1992.
A. Rosenfeld, “The fuzzy geometry of image subset”, Pattern Recognition Letters, vol. 2, pp. 311–317, 1984.
P.C. Smits and S.G. Dellepiane, “Synthetic Aperture Radar image segmentation by a detail preserving Markov Random Field approach”, IEEE Transactions on Geoscience and Remote Sensing, vol. 35, no. 4, pp. 844–857, 1997.
P.C. Smits and S. Dellepiane, “Irregular MRF region label model for multichannel image segmentation”, Pattern Recognition Letters vol. 18, no. 11–13, pp. 1133–1142, 1997.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin · Heidelberg
About this paper
Cite this paper
Dellepiane, S. (1999). Detail-Preserving Processing of Remote Sensing Images. In: Kanellopoulos, I., Wilkinson, G.G., Moons, T. (eds) Machine Vision and Advanced Image Processing in Remote Sensing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60105-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-60105-7_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-64260-9
Online ISBN: 978-3-642-60105-7
eBook Packages: Springer Book Archive