{"title":"扫描探针显微镜图像的恢复","authors":"G. Pingali, R. Jain","doi":"10.1109/ACV.1992.240301","DOIUrl":null,"url":null,"abstract":"Scanning probe microscopy (SXM), which includes techniques such as scanning tunneling microscopy (STM) and scanning force microscopy (SFM), is becoming popular for 3D metrology in the semiconductor industry and for high resolution 3D imaging of surfaces in Materials Science and Biology. The authors present imaging models for SXM that take into account the effect of probe geometry on topographic images produced by SXM in 'contact' and 'non-contact' modes. The authors formulate methods for restoring an SXM image to obtain the original surface. Criteria for determining certainty of restoration are developed. It is shown that the methods developed can be expressed in terms of gray scale morphological operators. The efficacy of the approach is demonstrated by applying it to synthetic and real data.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":" 736","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"Restoration of scanning probe microscope images\",\"authors\":\"G. Pingali, R. Jain\",\"doi\":\"10.1109/ACV.1992.240301\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Scanning probe microscopy (SXM), which includes techniques such as scanning tunneling microscopy (STM) and scanning force microscopy (SFM), is becoming popular for 3D metrology in the semiconductor industry and for high resolution 3D imaging of surfaces in Materials Science and Biology. The authors present imaging models for SXM that take into account the effect of probe geometry on topographic images produced by SXM in 'contact' and 'non-contact' modes. The authors formulate methods for restoring an SXM image to obtain the original surface. Criteria for determining certainty of restoration are developed. It is shown that the methods developed can be expressed in terms of gray scale morphological operators. The efficacy of the approach is demonstrated by applying it to synthetic and real data.<<ETX>>\",\"PeriodicalId\":153393,\"journal\":{\"name\":\"[1992] Proceedings IEEE Workshop on Applications of Computer Vision\",\"volume\":\" 736\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1992] Proceedings IEEE Workshop on Applications of Computer Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACV.1992.240301\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACV.1992.240301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scanning probe microscopy (SXM), which includes techniques such as scanning tunneling microscopy (STM) and scanning force microscopy (SFM), is becoming popular for 3D metrology in the semiconductor industry and for high resolution 3D imaging of surfaces in Materials Science and Biology. The authors present imaging models for SXM that take into account the effect of probe geometry on topographic images produced by SXM in 'contact' and 'non-contact' modes. The authors formulate methods for restoring an SXM image to obtain the original surface. Criteria for determining certainty of restoration are developed. It is shown that the methods developed can be expressed in terms of gray scale morphological operators. The efficacy of the approach is demonstrated by applying it to synthetic and real data.<>