{"title":"虚拟显微镜亚像素图像拼接的正弦插值方法","authors":"Gökhan Baş, G.K. Demir","doi":"10.1109/BIYOMUT.2010.5479798","DOIUrl":null,"url":null,"abstract":"This study involves a two-step approach to the stitching of images taken for virtual microscopy application. The method has a sub-pixel resolution. To achieve this, first, a coarse shift level is adopted via a correlation function, and then a sinc interpolation is applied to the small neighborhood region of this coarse point. At the end, the sub-pixel shift level is determined by obtaining the maximum of the interpolated function using a gradient descent algorithm. Image stitching process is finalized with linear blending. Results are obtained within the range of ten percent subpixel tolerance.","PeriodicalId":180275,"journal":{"name":"2010 15th National Biomedical Engineering Meeting","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sinc interpolating approach to sub-pixel image stitching for virtual microscopy\",\"authors\":\"Gökhan Baş, G.K. Demir\",\"doi\":\"10.1109/BIYOMUT.2010.5479798\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study involves a two-step approach to the stitching of images taken for virtual microscopy application. The method has a sub-pixel resolution. To achieve this, first, a coarse shift level is adopted via a correlation function, and then a sinc interpolation is applied to the small neighborhood region of this coarse point. At the end, the sub-pixel shift level is determined by obtaining the maximum of the interpolated function using a gradient descent algorithm. Image stitching process is finalized with linear blending. Results are obtained within the range of ten percent subpixel tolerance.\",\"PeriodicalId\":180275,\"journal\":{\"name\":\"2010 15th National Biomedical Engineering Meeting\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 15th National Biomedical Engineering Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIYOMUT.2010.5479798\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 15th National Biomedical Engineering Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIYOMUT.2010.5479798","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sinc interpolating approach to sub-pixel image stitching for virtual microscopy
This study involves a two-step approach to the stitching of images taken for virtual microscopy application. The method has a sub-pixel resolution. To achieve this, first, a coarse shift level is adopted via a correlation function, and then a sinc interpolation is applied to the small neighborhood region of this coarse point. At the end, the sub-pixel shift level is determined by obtaining the maximum of the interpolated function using a gradient descent algorithm. Image stitching process is finalized with linear blending. Results are obtained within the range of ten percent subpixel tolerance.