{"id":167976,"date":"1994-09-01T00:00:00","date_gmt":"1994-09-01T00:00:00","guid":{"rendered":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/msr-research-item\/decision-based-median-filter-using-local-signal-statistics\/"},"modified":"2018-10-16T20:03:42","modified_gmt":"2018-10-17T03:03:42","slug":"decision-based-median-filter-using-local-signal-statistics","status":"publish","type":"msr-research-item","link":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/decision-based-median-filter-using-local-signal-statistics\/","title":{"rendered":"Decision-based median filter using local signal statistics"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Noise removal is important in many applications. When the noise has impulsive characteristics, linear techniques do not perform well, and median filter or its derivatives are often used. Although median-based filters preserve edges reasonably well, they tend to remove some of the finer details in the image. Switching schemes&#8211;where the filter is switched between two or more filters&#8211;have been proposed, but they usually lack a decision rule efficient enough to yield good results on different regions of the image. In this paper we present a strategy to overcome this problem. A decision rule based on the second order local statistics of the signal (within a window) is used to switch between the identity filter and a median filter. The results on a test image show an improvement of around 4 dB over the median filter alone, and 2 dB over other techniques.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Noise removal is important in many applications. When the noise has impulsive characteristics, linear techniques do not perform well, and median filter or its derivatives are often used. Although median-based filters preserve edges reasonably well, they tend to remove some of the finer details in the image. Switching schemes&#8211;where the filter is switched between two [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"SPIE","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"Proceedings SPIE 2308, Visual Communications and Image Processing '94","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"268","msr_page_range_start":"268","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"Proceedings SPIE 2308, Visual Communications and Image Processing '94","msr_doi":"10.1117\/12.185969","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Ronald 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