{"title":"Sub-window inverse distance weighting method for removing salt-and-pepper noise","authors":"Chaipichit Cumpim, R. Punchalard","doi":"10.1109/IEECON.2017.8075883","DOIUrl":null,"url":null,"abstract":"In this paper, the inverse distance weighting (IDW) is utilized in order to restore contaminated images which are corrupted by the salt-and-pepper noise (SPN). Our method consists of three steps. The first step, the noise candidate pixels are identified by the adaptive median filter. For the second step, the noisy image is divided into many sub-windows. The last step, for each sub-window from previous step, the IDW is applied to calculate the new pixel values that use the neighbour uncorrupted pixels in each sub-region. The results of experiments demonstrate that the proposed technique is better performance than the existing methods.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Electrical Engineering Congress (iEECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEECON.2017.8075883","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, the inverse distance weighting (IDW) is utilized in order to restore contaminated images which are corrupted by the salt-and-pepper noise (SPN). Our method consists of three steps. The first step, the noise candidate pixels are identified by the adaptive median filter. For the second step, the noisy image is divided into many sub-windows. The last step, for each sub-window from previous step, the IDW is applied to calculate the new pixel values that use the neighbour uncorrupted pixels in each sub-region. The results of experiments demonstrate that the proposed technique is better performance than the existing methods.