dc.contributor.authorMiao, Zhenwei
dc.contributor.authorJiang, Xudong
dc.date.accessioned2013-10-23T04:33:53Z
dc.date.available2013-10-23T04:33:53Z
dc.date.copyright2013en_US
dc.date.issued2013
dc.identifier.citationMiao, Z., & Jiang, X. (2013). Weighted iterative truncated mean filter. IEEE Transactions on Signal Processing, 61(16), 4149-4160.en_US
dc.identifier.issn1053-587Xen_US
dc.identifier.urihttp://hdl.handle.net/10220/16692
dc.description.abstractThe iterative truncated arithmetic mean (ITM) filter was proposed recently. It offers a way to estimate the sample median by simple arithmetic computing instead of the time consuming data sorting. In this paper, a rich class of filters named weighted ITM (WITM) filters are proposed. By iteratively truncating the extreme samples, the output of the WITM filter converges to the weighted median. Proper stopping criterion makes the WITM filters own merits of both the weighted mean and median filters and hence outperforms the both in some applications. Three structures are designed to enable the WITM filters being low-, band- and high-pass filters. Properties of these filters are presented and analyzed. Experimental evaluations are carried out on both synthesis and real data to verify some properties of the WITM filters.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesIEEE Transactions on Signal Processingen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering
dc.titleWeighted iterative truncated mean filteren_US
dc.typeJournal Article
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1109/TSP.2013.2267739


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