{"title":"Estimation of affine transformations between images pairs via Fourier transform","authors":"L. Lucchese, G. Cortelazzo, C. M. Monti","doi":"10.1109/ICIP.1996.560780","DOIUrl":null,"url":null,"abstract":"This article presents an original algorithm operating in the frequency domain for estimating the affine transformation between a pair of images. The affine matrix is estimated by the relationships between companion stretched slices of the Fourier transforms magnitudes of the two images. The translational vector is estimated by phase-correlation after compensating for the contribution of the affine matrix. This approach is \"global\" in the sense that it uses the whole images information and it does not rest upon features extraction and matching. It can be efficiently implemented via FFT and it is suited to unsupervised estimation of affine transformations. Experimental evidence of the effectiveness and robustness of the proposed method is reported.","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd IEEE International Conference on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.1996.560780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
This article presents an original algorithm operating in the frequency domain for estimating the affine transformation between a pair of images. The affine matrix is estimated by the relationships between companion stretched slices of the Fourier transforms magnitudes of the two images. The translational vector is estimated by phase-correlation after compensating for the contribution of the affine matrix. This approach is "global" in the sense that it uses the whole images information and it does not rest upon features extraction and matching. It can be efficiently implemented via FFT and it is suited to unsupervised estimation of affine transformations. Experimental evidence of the effectiveness and robustness of the proposed method is reported.