Noise and speckle reduction in synthetic aperture radar imagery by nonparametric Wiener filtering.

We present a Wiener filter that is especially suitable for speckle and noise reduction in multilook synthetic aperture radar (SAR) imagery. The proposed filter is nonparametric, not being based on parametrized analytical models of signal statistics. Instead, the Wiener-Hopf equation is expressed entirely in terms of observed signal statistics, with no reference to the possibly unobservable pure signal and noise. This Wiener filter is simple in concept and implementation, exactly minimum mean-square error, and directly applicable to signal-dependent and multiplicative noise. We demonstrate the filtering of a genuine two-look SAR image and show how a nonnegatively constrained version of the filter substantially reduces ringing.

[1]  Leonard J. Porcello,et al.  Speckle reduction in synthetic-aperture radars , 1976 .

[2]  J. Goodman Some fundamental properties of speckle , 1976 .

[3]  C. Helstrom Image Restoration by the Method of Least Squares , 1967 .

[4]  Daniel N. Held,et al.  Comparison of Several Techniques to Obtain Multiple-Look SAR Imagery , 1983, IEEE Transactions on Geoscience and Remote Sensing.

[5]  A A Sawchuk,et al.  Noise updating repeated Wiener filter and other adaptive noise smoothing filters using local image statistics. , 1986, Applied optics.

[6]  David G. Long,et al.  Azimuthal modulation of C-band scatterometer σ0 over Southern Ocean sea ice , 1997, IEEE Trans. Geosci. Remote. Sens..

[7]  Robert S. Caprari Generalized matched filters and univariate Neyman-Pearson detectors for image target detection , 2000, IEEE Trans. Inf. Theory.

[8]  Reginald L. Lagendijk,et al.  Regularized iterative image restoration with ringing reduction , 1988, IEEE Trans. Acoust. Speech Signal Process..

[9]  Yu Cao,et al.  Cross Burg entropy maximization and its application to ringing suppression in image reconstruction , 1999, IEEE Trans. Image Process..

[10]  E. M. Bracalente,et al.  σ° Signature of the Amazon Rain Forest Obtained from the Seasat Scatterometer , 1982, IEEE Transactions on Geoscience and Remote Sensing.

[11]  E R Harvey,et al.  Speckle reduction in synthetic-aperture-radar imagery. , 1990, Optics letters.

[12]  Joseph W. Goodman A random walk through the field of speckle , 1986 .

[13]  R. S. Caprari Non-parametric Wiener filter for reducing noise on reproducible pure signals , 1999 .

[14]  A. Murat Tekalp,et al.  Edge-adaptive Kalman filtering for image restoration with ringing suppression , 1989, IEEE Trans. Acoust. Speech Signal Process..

[15]  Stephen E. Reichenbach,et al.  Small convolution kernels for high-fidelity image restoration , 1991, IEEE Trans. Signal Process..

[16]  Victor S. Frost,et al.  A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  N.J.S. Stacy,et al.  Ingara: an integrated airborne imaging radar system , 1996, IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium.

[18]  G. Franceschetti,et al.  Iterative homomorphic technique for speckle reduction in synthetic-aperture radar imaging , 1995 .

[19]  R. Unbehauen,et al.  Estimation of image noise variance , 1999 .