{"title":"强大的对焦测距","authors":"Hari N. Nair, C. Stewart","doi":"10.1109/CVPR.1992.223258","DOIUrl":null,"url":null,"abstract":"Depth maps obtained from focus ranging can have numerous errors and distortions due to edge bleeding, feature shifts, image noise, and field curvature. An improved algorithm that examines an initial high depth-of-field image of the scene to identify regions susceptible to edge bleeding and image noise is given. Focus evaluation windows are adapted to local image content and optimize the tradeoff between spatial resolution and noise sensitivity. An elliptical paraboloid field curvature model is used to reduce range distortion in peripheral image areas. Spatio-temporal tracking compensates for image feature shifts. The result is a sparse but reliable depth map.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"57","resultStr":"{\"title\":\"Robust focus ranging\",\"authors\":\"Hari N. Nair, C. Stewart\",\"doi\":\"10.1109/CVPR.1992.223258\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Depth maps obtained from focus ranging can have numerous errors and distortions due to edge bleeding, feature shifts, image noise, and field curvature. An improved algorithm that examines an initial high depth-of-field image of the scene to identify regions susceptible to edge bleeding and image noise is given. Focus evaluation windows are adapted to local image content and optimize the tradeoff between spatial resolution and noise sensitivity. An elliptical paraboloid field curvature model is used to reduce range distortion in peripheral image areas. Spatio-temporal tracking compensates for image feature shifts. The result is a sparse but reliable depth map.<<ETX>>\",\"PeriodicalId\":325476,\"journal\":{\"name\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"57\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPR.1992.223258\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.1992.223258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Depth maps obtained from focus ranging can have numerous errors and distortions due to edge bleeding, feature shifts, image noise, and field curvature. An improved algorithm that examines an initial high depth-of-field image of the scene to identify regions susceptible to edge bleeding and image noise is given. Focus evaluation windows are adapted to local image content and optimize the tradeoff between spatial resolution and noise sensitivity. An elliptical paraboloid field curvature model is used to reduce range distortion in peripheral image areas. Spatio-temporal tracking compensates for image feature shifts. The result is a sparse but reliable depth map.<>