C. Brauer-Burchardt, Stephan Schroder, M. Trost, P. Kuhmstedt, A. Duparré, G. Notni
{"title":"Roughness determination of ultra thin multilayer coatings in cross-section images with poor SNR using edge localization","authors":"C. Brauer-Burchardt, Stephan Schroder, M. Trost, P. Kuhmstedt, A. Duparré, G. Notni","doi":"10.1109/ISPA.2009.5297744","DOIUrl":null,"url":null,"abstract":"The interface roughness of multilayer coatings consisting of ultra thin alternating layers strongly influences the optical properties of dielectric mirrors. However, the technical possibilities for its characterization are limited. In this paper a new method for roughness determination of multilayer systems based on cross-section images is introduced. The core of the method is a new edge localization algorithm which is very robust even in the case of very low signal to noise ratio below three. Accuracy analysis is given and results are presented.","PeriodicalId":382753,"journal":{"name":"2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis","volume":"526 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2009.5297744","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 interface roughness of multilayer coatings consisting of ultra thin alternating layers strongly influences the optical properties of dielectric mirrors. However, the technical possibilities for its characterization are limited. In this paper a new method for roughness determination of multilayer systems based on cross-section images is introduced. The core of the method is a new edge localization algorithm which is very robust even in the case of very low signal to noise ratio below three. Accuracy analysis is given and results are presented.