Mahmoud Saeidi, S. Motamedi, A. Behrad, B. Saeidi, R. Saeidi, Reza Saeidi
{"title":"Noise reduction of consecutive images using a new adaptive weighted averaging filter","authors":"Mahmoud Saeidi, S. Motamedi, A. Behrad, B. Saeidi, R. Saeidi, Reza Saeidi","doi":"10.1109/SIPS.2005.1579912","DOIUrl":null,"url":null,"abstract":"In this paper, we will propose a novel spatiotemporal filter that utilizes consecutive frames in order to remove noise. The consecutive frames include: current, previous and next noisy frames. The filter proposed in this paper is based upon the weighted averaging pixels intensity in image sequences. The weights are determined by a well-defined mathematical criterion, which is adaptive to the feature of spatiotemporal pixels of the consecutive frames. It is experimentally shown that the proposed filter can preserve image structures and edges under motion while suppressing noise, and thus can be effectively used in image sequences filtering. Most importantly, our proposed filter is independent of noise variance and only utilizes the intensity of pixels to suppress noise.","PeriodicalId":436123,"journal":{"name":"IEEE Workshop on Signal Processing Systems Design and Implementation, 2005.","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Workshop on Signal Processing Systems Design and Implementation, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIPS.2005.1579912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper, we will propose a novel spatiotemporal filter that utilizes consecutive frames in order to remove noise. The consecutive frames include: current, previous and next noisy frames. The filter proposed in this paper is based upon the weighted averaging pixels intensity in image sequences. The weights are determined by a well-defined mathematical criterion, which is adaptive to the feature of spatiotemporal pixels of the consecutive frames. It is experimentally shown that the proposed filter can preserve image structures and edges under motion while suppressing noise, and thus can be effectively used in image sequences filtering. Most importantly, our proposed filter is independent of noise variance and only utilizes the intensity of pixels to suppress noise.