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Model-based despeckling and information extraction from SAR images
2000
IEEE Transactions on Geoscience and Remote Sensing
Basic textures as they appear, especially in high resolution SAR images, are affected by multiplicative speckle noise and should be preserved by despeckling algorithms. Sharp edges between different regions and strong scatterers also must be preserved. To despeckle images, we use a maximum a posteriori (MAP) estimation of the cross section, choosing between different prior models. The proposed approach uses a Gauss Markov random field (GMRF) model for textured areas and allows an adaptive
doi:10.1109/36.868883
fatcat:4ssfvgznkrelllhkuwotqdn5me