Estimating Asymmetric Noise
نویسندگان
چکیده
Recent work is summarised that characterises deterministically and statistically the performance of morphological and rank order filters. We propose adaptivtly filtering noise that is asymmetric by one of the biased morphological filters co and oc whose average is known to be an unbiased estimator of a signal in symmetric noise. Significant differences in filtered images are determined using a nonparametric statistical test. Preliminary results illustrating the theory and applying it to texture segmentation are presented.
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