A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise

Authors:
Victor S. Frost;Josephine Abbott Stiles;K. S. Shanmugan;Julian C. Holtzman
Affiliations:
STUDENT MEMBER, IEEE, Remote Sensing Laboratory, Center for Research, Inc., University of Kansas, Lawrence, KS 66045.;STUDENT MEMBER, IEEE, Remote Sensing Laboratory, Center for Research, Inc., University of Kansas, Lawrence, KS 66045.;SENIOR MEMBER, IEEE, Remote Sensing Laboratory, Center for Research, Inc., University of Kansas, Lawrence, KS 66045.;MEMBER, IEEE, Remote Sensing Laboratory, Center for Research, Inc., University of Kansas, Lawrence, KS 66045.
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1982

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Abstract

Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.