Abstract
In this paper, we study the behaviour of contour recovery when filtering radar images. We start from recent methods lying on an equivalence scheme between implicit and explicit boundary processes in image restoration [1, 2]. Here we extend them to the processing of synthetic aperture radar (SAR) images. First we set up a general bayesian frame enabling recovery of discontinuities in such restoration methods. Then we exhibit an extension of the Geman-Reynolds-Charbonnier theorem allowing convenient filtering of SAR images. Due to the high dynamics of radar ERS-1 images, a deterministic algorithm is proposed integrating different statistical hypotheses for observation and regularization parts. Besides, we use a well-adapted SAR edge detector instead of the usual gradient in the boundary estimation step of an iterative boundary/intensity restoration algorithm. Intensities are then estimated with a deterministic non-linear method. Finally, the particular behaviour or radar statistics (χ law) lead us to define a new potential function adapted to speckle regularization while respecting region discontinuities.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
D. Geman and G. Reynolds. Constrained restoration and the recovery of discontinuities. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(3), March 1992.
P. Charbonnier, L. Blanc-Féraud, G. Aubert and M. Barlaud. Deterministic Edge-Preserving Regularization in Computed Imaging. IEEE Transactions on Image Processing, 5(12):1–13, 1996.
A. Blake and A. Zissermann. Visual Reconstruction. MIT Press, 1987.
M. Nikolova, A. Mohammad-Djaffari, and J. Idier. Inversion of large-support illconditioned linear operators using a markov model with a line process. IEEE Transactions on Acoustic Speech and Signal Processing, 5:357–360, 1994.
J. Zerubia and R. Chellapa. Mean Field Annealing for Edge Detection and Image Restoration. Signal Processing V: Theories and Applications. L. Torres, E. Masgrau and M.A. Lagunas (eds.) Elsevier Science Publishers B.V. 837–840, 1990.
D. Geiger and F. Girosi. Parallel and deterministic algorithms from MRF's: surface reconstruction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(5), 1991.
Geometry-Driven Diffusion in Computer Vision. Editor: Bart M. ter Haar Romeny, Kluwer Academic Publishers, 1994.
S. Geman and D. Geman. Stochastic relaxation, Gibbs distribution, and the bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6(6):721–741, 1984.
L. Bedini, I. Gerace, and A. Tonazzini. A deterministic algorithm for reconstructing images with interactive discontinuities. Computer Vision and Graphics Image Processing: Graphical Models and Image Processing, 56(2):109–123, 1993.
J.-S. Lee. Speckle analysis and smoothing of synthetic aperture radar images. Computer Graphics and Image Processing, 17:24–32, 1981.
Kuan, Sawchuk, Strand, and Chavel. Adaptive restoration of images with speckle. IEEE Transactions on Acoustics, Speech, and Signal Processing, ASSP-35(3):373–383, 1987.
Y. Wu and H. MaÎtre. Smoothing speckled synthetic aperture radar images by using maximum homogeneous region filters. Optical Engineering, 31(8): 1785–1792, 1992.
A. Lopes, E. Nezry, R. Touzi, and H. Laur. Structure detection, and statistical adaptive filtering in SAR images. Int. J. Remote Sensing, 14(9):1735–1758, 1993.
F.-K. Li, C. Croft, and D. N. Held. Comparison of several techniques to obtain multiple-look SAR imagery. IEEE Transactions on Geoscience and Remote sensing, GE-21(3):370–375, July 1983.
J.W Goodman. Statistical properties of laser speckle patterns. In Laser Speckle and Related Phenomena, volume 9, pages 9–75. J.C Dainty (Springer Verlag, Heidelberg, 1975), 1975.
M. Abramowitz and I. Stegun. Handbook of Mathematical Functions. Dover Publications, 1972.
E. Jakeman and Tough J. A. Generalized K distribution: a statistical model for weak scattering. J. Opt. Soc. Am., 4(9):1764–1772, 1987.
C. J. Oliver. A model for non-Rayleigh scattering statistics. Optica Acta, 31(6):701–722, 1984.
A. C. Bovik. On detecting edges in speckle imagery. IEEE Transactions on Acoustics, Speech and Signal Processing, ASSP-36(10): 1618–1627, October 1988.
R. Touzi, A. Lopes, and P. Bousquet. A statistical and geometrical edge detector for SAR images. IEEE Transactions on Geoscience And Remote Sensing, TGARS-26(6):764–773, November 1988.
J.W. Goodman. Some fundamental properties of speckle. Journal Optical Society of America, 66(11):1145–1150, 1976.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tupin, F., Sigelle, M., Chkeif, A., Véran, JP. (1997). Restoration of SAR images using recovery of discontinuities and non-linear optimization. In: Pelillo, M., Hancock, E.R. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 1997. Lecture Notes in Computer Science, vol 1223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62909-2_73
Download citation
DOI: https://doi.org/10.1007/3-540-62909-2_73
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-62909-2
Online ISBN: 978-3-540-69042-9
eBook Packages: Springer Book Archive