{"title":"基于小波的体积变形","authors":"Taosong He, Sidney W. Wang, A. Kaufman","doi":"10.1109/VISUAL.1994.346333","DOIUrl":null,"url":null,"abstract":"This paper presents a technique for performing volume morphing between two volumetric datasets in the wavelet domain. The idea is to decompose the volumetric datasets into a set of frequency bands, apply smooth interpolation to each band, and reconstruct to form the morphed model. In addition, a technique for establishing a suitable correspondence among object voxels is presented. The combination of these two techniques results in a smooth transition between the two datasets and produces morphed volume with fewer high frequency distortions than those obtained from spatial domain volume morphing.<<ETX>>","PeriodicalId":273215,"journal":{"name":"Proceedings Visualization '94","volume":"547 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"153","resultStr":"{\"title\":\"Wavelet-based volume morphing\",\"authors\":\"Taosong He, Sidney W. Wang, A. Kaufman\",\"doi\":\"10.1109/VISUAL.1994.346333\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a technique for performing volume morphing between two volumetric datasets in the wavelet domain. The idea is to decompose the volumetric datasets into a set of frequency bands, apply smooth interpolation to each band, and reconstruct to form the morphed model. In addition, a technique for establishing a suitable correspondence among object voxels is presented. The combination of these two techniques results in a smooth transition between the two datasets and produces morphed volume with fewer high frequency distortions than those obtained from spatial domain volume morphing.<<ETX>>\",\"PeriodicalId\":273215,\"journal\":{\"name\":\"Proceedings Visualization '94\",\"volume\":\"547 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"153\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Visualization '94\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VISUAL.1994.346333\",\"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 Visualization '94","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VISUAL.1994.346333","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a technique for performing volume morphing between two volumetric datasets in the wavelet domain. The idea is to decompose the volumetric datasets into a set of frequency bands, apply smooth interpolation to each band, and reconstruct to form the morphed model. In addition, a technique for establishing a suitable correspondence among object voxels is presented. The combination of these two techniques results in a smooth transition between the two datasets and produces morphed volume with fewer high frequency distortions than those obtained from spatial domain volume morphing.<>