{"title":"Adaptive pixel targeting and filtering with adjacency variations in second-order derivatives of pixel values for SEM images","authors":"W. T. Chan, Kok-Swee Sim","doi":"10.1109/ICORAS.2016.7872624","DOIUrl":null,"url":null,"abstract":"The proposed method utilizes histograms of second-order derivatives of the values of the pixels in an SEM image. The histograms of second-order values can express the variation in pixel values due to the effect of noise. The histograms are used as the basis for a technique to target pixels for filtering. To control the number of pixels which are targeted so as to minimize blurring of edges, a curve-fitted profile is imposed on the histograms in order to select pixels based on the differences between their second-order derivatives and those of their neighbours. The proposed method is found to be more effective at higher levels of additive noise.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICORAS.2016.7872624","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
The proposed method utilizes histograms of second-order derivatives of the values of the pixels in an SEM image. The histograms of second-order values can express the variation in pixel values due to the effect of noise. The histograms are used as the basis for a technique to target pixels for filtering. To control the number of pixels which are targeted so as to minimize blurring of edges, a curve-fitted profile is imposed on the histograms in order to select pixels based on the differences between their second-order derivatives and those of their neighbours. The proposed method is found to be more effective at higher levels of additive noise.