{"title":"Phase unwrapping using vector space projection methods","authors":"B. Marendic, H. Stark, Yongyi Yang","doi":"10.1109/EIT.2005.1627047","DOIUrl":null,"url":null,"abstract":"In this paper we explore a new approach for unwrapping of two-dimensional phase functions using vector-space projection methods. Phase unwrapping is essential for imaging systems that construct the image from phase information. Unlike some existing methods where unwrapping is performed locally on a piece-by-piece basis, this work approaches the unwrapping problem from a global point of view. The unwrapping is done iteratively, based on an extension of the Gerchberg-Papoulis algorithm, and the solution is refined over the entire region of support at each iteration. Robustness is demonstrated through its performance in a noisy environment, and its performance is compared to the least-squares algorithm developed by Pritt","PeriodicalId":358002,"journal":{"name":"2005 IEEE International Conference on Electro Information Technology","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE International Conference on Electro Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIT.2005.1627047","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 we explore a new approach for unwrapping of two-dimensional phase functions using vector-space projection methods. Phase unwrapping is essential for imaging systems that construct the image from phase information. Unlike some existing methods where unwrapping is performed locally on a piece-by-piece basis, this work approaches the unwrapping problem from a global point of view. The unwrapping is done iteratively, based on an extension of the Gerchberg-Papoulis algorithm, and the solution is refined over the entire region of support at each iteration. Robustness is demonstrated through its performance in a noisy environment, and its performance is compared to the least-squares algorithm developed by Pritt