Statistical soft morphology is an extension of soft morphology which is based on a probabilistic model. It has been first proposed for 1D signal processing. In this paper the 2D case is considered which can be useful to solve image processing restoration problems. Statistical soft morphological operators provide good result in cleaning noise with both morphological and statistical structures, such as speckle noise. Results are presented which show that the proposed method is suitable for processing remote sensing images.
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