{"title":"三剪三维旋转","authors":"Tommaso Toffoli , Jason Quick","doi":"10.1006/gmip.1997.0420","DOIUrl":null,"url":null,"abstract":"<div><p>We show that a rotation in three dimensions can be achieved by a composition of three shears, the first and third along a specified axis and the second along another given axis orthogonal to the first; this process is invertible. The resulting rotation algorithm is practical for the processing of fine-grained digital images, and is well adapted to the access constraints of common storage media such as dynamic<em>RAM</em>or magnetic disk. For a 2-D image, rotation by composition of three shears is well known. For 3-D, an obvious nine-shear decomposition has been mentioned in the literature. Our three-shear decomposition is a sizable improvement over that, and is the best that can be attained—just two shears won't do. Also, we give a brief summary of how the present three-shear decomposition approach generalizes to any linear transformations of unit determinant in any number of dimensions.</p></div>","PeriodicalId":100591,"journal":{"name":"Graphical Models and Image Processing","volume":"59 2","pages":"Pages 89-95"},"PeriodicalIF":0.0000,"publicationDate":"1997-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/gmip.1997.0420","citationCount":"43","resultStr":"{\"title\":\"Three-Dimensional Rotations by Three Shears\",\"authors\":\"Tommaso Toffoli , Jason Quick\",\"doi\":\"10.1006/gmip.1997.0420\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We show that a rotation in three dimensions can be achieved by a composition of three shears, the first and third along a specified axis and the second along another given axis orthogonal to the first; this process is invertible. The resulting rotation algorithm is practical for the processing of fine-grained digital images, and is well adapted to the access constraints of common storage media such as dynamic<em>RAM</em>or magnetic disk. For a 2-D image, rotation by composition of three shears is well known. For 3-D, an obvious nine-shear decomposition has been mentioned in the literature. Our three-shear decomposition is a sizable improvement over that, and is the best that can be attained—just two shears won't do. Also, we give a brief summary of how the present three-shear decomposition approach generalizes to any linear transformations of unit determinant in any number of dimensions.</p></div>\",\"PeriodicalId\":100591,\"journal\":{\"name\":\"Graphical Models and Image Processing\",\"volume\":\"59 2\",\"pages\":\"Pages 89-95\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1006/gmip.1997.0420\",\"citationCount\":\"43\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Graphical Models and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1077316997904202\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Graphical Models and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1077316997904202","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We show that a rotation in three dimensions can be achieved by a composition of three shears, the first and third along a specified axis and the second along another given axis orthogonal to the first; this process is invertible. The resulting rotation algorithm is practical for the processing of fine-grained digital images, and is well adapted to the access constraints of common storage media such as dynamicRAMor magnetic disk. For a 2-D image, rotation by composition of three shears is well known. For 3-D, an obvious nine-shear decomposition has been mentioned in the literature. Our three-shear decomposition is a sizable improvement over that, and is the best that can be attained—just two shears won't do. Also, we give a brief summary of how the present three-shear decomposition approach generalizes to any linear transformations of unit determinant in any number of dimensions.