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.
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© 1997 Springer-Verlag Berlin Heidelberg
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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
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DOI: https://doi.org/10.1007/3-540-62909-2_73
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