NDLI: Segmentation-Based MAP Despeckling of SAR Images in the Undecimated Wavelet Domain

Content Provider	IEEE Xplore Digital Library
Author	Bianchi, T. Argenti, F. Alparone, L.
Copyright Year	1980
Abstract	In this paper, a novel despeckling algorithm based on undecimated wavelet decomposition and maximum a posteriori estimation is proposed. Such a method represents an improvement with respect to the filter presented by the authors, and it is based on the same conjecture that the probability density functions (pdfs) of the wavelet coefficients follow a generalized Gaussian (GG) distribution. However, the approach introduced here presents two major novelties: 1) theoretically exact expressions for the estimation of the GG parameters are derived: such expressions do not require further assumptions other than the multiplicative model with uncorrelated speckle, and hold also in the case of a strongly correlated reflectivity; 2) a model for the classification of the wavelet coefficients according to their texture energy is introduced. This model allows us to classify the wavelet coefficients into classes having different degrees of heterogeneity, so that ad hoc estimation approaches can be devised for the different sets of coefficients. Three different implementations, characterized by different approaches for incorporating into the filtering procedure the information deriving from the segmentation of the wavelet coefficients, are proposed. Experimental results, carried out on both artificially speckled images and true synthetic aperture radar images, demonstrate that the proposed filtering approach outperforms the previous filters, irrespective of the features of the underlying reflectivity.
Sponsorship	IEEE Geoscience and Remote Sensing Society IEEE URSI
Starting Page	2728
Ending Page	2742
Page Count	15
File Size	2034824
File Format	PDF
ISSN	01962892
Volume Number	46
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Wavelet domain Filtering Wavelet coefficients Signal resolution Reflectivity Spatial resolution Additive noise Filters Signal to noise ratio undecimated wavelet decomposition Despeckling generalized Gaussian (GG) modeling image segmentation synthetic aperture radar (SAR)
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Electrical and Electronic Engineering

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