In this paper, a new despeckling method based on undecimated wavelet decomposition and maximum a posteriori (MAP) estimation is proposed. Such a method relies on the assumption that the probability density function (PDF) of each wavelet coefficient is generalized Gaussian (GG). The major novelty of the proposed approach is that the parameters of the GG PDF are taken to be space-varying within each wavelet frame. Thus, they may be adjusted to spatial image context, not only to scale and orientation. Since the MAP equation to be solved is a function of the parameters of the assumed PDF model, the variance and shape factor of the GG function are derived from the theoretical moments, which depend on the moments and joint moments of the observed noisy signal and on the statistics of speckle. The solution of the MAP equation yields the MAP estimate of the wavelet coefficients of the noise-free image. The restored SAR image is synthesized from such coefficients. Experimental results, carried out on both synthetic speckled images and true SAR images, demonstrate that MAP filtering can be successfully applied to SAR images represented in the shift-invariant wavelet domain, without resorting to a logarithmic transformation.

A new multiresolution approach to MAP despeckling of SAR imagery / L. Alparone;F. Argenti;T. Bianchi. - STAMPA. - (2006), pp. 4000-4003. (Intervento presentato al convegno 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS tenutosi a Denver, CO nel 31 July-4 Aug. 2006) [10.1109/IGARSS.2006.1026].

A new multiresolution approach to MAP despeckling of SAR imagery

ALPARONE, LUCIANO;ARGENTI, FABRIZIO;BIANCHI, TIZIANO
2006

Abstract

In this paper, a new despeckling method based on undecimated wavelet decomposition and maximum a posteriori (MAP) estimation is proposed. Such a method relies on the assumption that the probability density function (PDF) of each wavelet coefficient is generalized Gaussian (GG). The major novelty of the proposed approach is that the parameters of the GG PDF are taken to be space-varying within each wavelet frame. Thus, they may be adjusted to spatial image context, not only to scale and orientation. Since the MAP equation to be solved is a function of the parameters of the assumed PDF model, the variance and shape factor of the GG function are derived from the theoretical moments, which depend on the moments and joint moments of the observed noisy signal and on the statistics of speckle. The solution of the MAP equation yields the MAP estimate of the wavelet coefficients of the noise-free image. The restored SAR image is synthesized from such coefficients. Experimental results, carried out on both synthetic speckled images and true SAR images, demonstrate that MAP filtering can be successfully applied to SAR images represented in the shift-invariant wavelet domain, without resorting to a logarithmic transformation.
2006
2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
Denver, CO
31 July-4 Aug. 2006
L. Alparone;F. Argenti;T. Bianchi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/521898
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