Gwanggil Jeon, M. Anisetti, V. Bellandi, E. Damiani, Jechang Jeong, I. Suh
{"title":"Robust Fuzzy Filter for Noise Reduction in Video Deinterlacing","authors":"Gwanggil Jeon, M. Anisetti, V. Bellandi, E. Damiani, Jechang Jeong, I. Suh","doi":"10.1109/SITIS.2008.30","DOIUrl":null,"url":null,"abstract":"This paper describes the design and evaluation of a robust noise reduction fuzzy filter, and considers its application to video deinterlacing. The proposed fuzzy filter is designed to reduce mixed noise (random and impulse) and to be used in real-time deinterlacing. The proposed algorithm consists of two main processes: an adaptive weighted fuzzy filter and an edge direction based deinterlacer. The proposed filter is easy to implement by applying a weighted membership function to an image within a window to compute the pixel at the center position.","PeriodicalId":202698,"journal":{"name":"2008 IEEE International Conference on Signal Image Technology and Internet Based Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Signal Image Technology and Internet Based Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITIS.2008.30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper describes the design and evaluation of a robust noise reduction fuzzy filter, and considers its application to video deinterlacing. The proposed fuzzy filter is designed to reduce mixed noise (random and impulse) and to be used in real-time deinterlacing. The proposed algorithm consists of two main processes: an adaptive weighted fuzzy filter and an edge direction based deinterlacer. The proposed filter is easy to implement by applying a weighted membership function to an image within a window to compute the pixel at the center position.