Pseudopolar-based estimation of large translations, rotations, and scalings in images
One of the major challenges related to image registration is the estimation of large motions without prior knowledge. This work presents a Fourier-based approach that estimates large translations, scalings, and rotations. The algorithm uses the pseudopolar (PP) Fourier transform to achieve substanti...
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| Published in | IEEE transactions on image processing Vol. 14; no. 1; pp. 12 - 22 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
IEEE
01.01.2005
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1057-7149 1941-0042 |
| DOI | 10.1109/TIP.2004.838692 |
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| Abstract | One of the major challenges related to image registration is the estimation of large motions without prior knowledge. This work presents a Fourier-based approach that estimates large translations, scalings, and rotations. The algorithm uses the pseudopolar (PP) Fourier transform to achieve substantial improved approximations of the polar and log-polar Fourier transforms of an image. Thus, rotations and scalings are reduced to translations which are estimated using phase correlation. By utilizing the PP grid, we increase the performance (accuracy, speed, and robustness) of the registration algorithms. Scales up to 4 and arbitrary rotation angles can be robustly recovered, compared to a maximum scaling of 2 recovered by state-of-the-art algorithms. The algorithm only utilizes one-dimensional fast Fourier transform computations whose overall complexity is significantly lower than prior works. Experimental results demonstrate the applicability of the proposed algorithms. |
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| AbstractList | One of the major challenges related to image registration is the estimation of large motions without prior knowledge. This work presents a Fourier-based approach that estimates large translations, scalings, and rotations. The algorithm uses the pseudopolar (PP) Fourier transform to achieve substantial improved approximations of the polar and log-polar Fourier transforms of an image. Thus, rotations and scalings are reduced to translations which are estimated using phase correlation. By utilizing the PP grid, we increase the performance (accuracy, speed, and robustness) of the registration algorithms. Scales up to 4 and arbitrary rotation angles can be robustly recovered, compared to a maximum scaling of 2 recovered by state-of-the-art algorithms. The algorithm only utilizes one-dimensional fast Fourier transform computations whose overall complexity is significantly lower than prior works. Experimental results demonstrate the applicability of the proposed algorithms. One of the major challenges related to image registration is the estimation of large motions without prior knowledge. This paper presents a Fourier-based approach that estimates large translations, scalings, and rotations. The algorithm uses the pseudopolar (PP) Fourier transform to achieve substantial improved approximations of the polar and log-polar Fourier transforms of an image. Thus, rotations and scalings are reduced to translations which are estimated using phase correlation. By utilizing the PP grid, we increase the performance (accuracy, speed, and robustness) of the registration algorithms. Scales up to 4 and arbitrary rotation angles can be robustly recovered, compared to a maximum scaling of 2 recovered by state-of-the-art algorithms. The algorithm only utilizes one-dimensional fast Fourier transform computations whose overall complexity is significantly lower than prior works. Experimental results demonstrate the applicability of the proposed algorithms.One of the major challenges related to image registration is the estimation of large motions without prior knowledge. This paper presents a Fourier-based approach that estimates large translations, scalings, and rotations. The algorithm uses the pseudopolar (PP) Fourier transform to achieve substantial improved approximations of the polar and log-polar Fourier transforms of an image. Thus, rotations and scalings are reduced to translations which are estimated using phase correlation. By utilizing the PP grid, we increase the performance (accuracy, speed, and robustness) of the registration algorithms. Scales up to 4 and arbitrary rotation angles can be robustly recovered, compared to a maximum scaling of 2 recovered by state-of-the-art algorithms. The algorithm only utilizes one-dimensional fast Fourier transform computations whose overall complexity is significantly lower than prior works. Experimental results demonstrate the applicability of the proposed algorithms. One of the major challenges related to image registration is the estimation of large motions without prior knowledge. This paper presents a Fourier-based approach that estimates large translations, scalings, and rotations. The algorithm uses the pseudopolar (PP) Fourier transform to achieve substantial improved approximations of the polar and log-polar Fourier transforms of an image. Thus, rotations and scalings are reduced to translations which are estimated using phase correlation. By utilizing the PP grid, we increase the performance (accuracy, speed, and robustness) of the registration algorithms. Scales up to 4 and arbitrary rotation angles can be robustly recovered, compared to a maximum scaling of 2 recovered by state-of-the-art algorithms. The algorithm only utilizes one-dimensional fast Fourier transform computations whose overall complexity is significantly lower than prior works. Experimental results demonstrate the applicability of the proposed algorithms. |
| Author | Keller, Y. Averbuch, A. Israeli, M. |
| Author_xml | – sequence: 1 givenname: Y. surname: Keller fullname: Keller, Y. organization: Dept. of Math., Yale Univ., New Haven, CT, USA – sequence: 2 givenname: A. surname: Averbuch fullname: Averbuch, A. – sequence: 3 givenname: M. surname: Israeli fullname: Israeli, M. |
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| Keywords | Image registration Fourier transformation Motion estimation Image processing Global motion estimation image alignment Algorithm Gradient method gradient methods subpixel registration |
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| References | ref13 ref12 ref15 ref14 ref11 ref1 Tekalp (ref2) 1995 ref17 Coifman (ref30) ref16 ref19 ref18 Averbuch (ref26) Oppenheim (ref24) 1998 ref25 ref20 ref22 ref21 ref28 Kuglin (ref10) ref29 ref8 ref7 ref9 ref4 ref3 Porat (ref23) 1997 Averbuch (ref27) ref6 ref5 |
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| SubjectTerms | Algorithms Applied sciences Artificial Intelligence Computer Graphics Discrete Fourier transforms Exact sciences and technology Fast Fourier transforms Fourier transforms Global motion estimation Gradient methods image alignment Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing Image registration Information Storage and Retrieval - methods Information, signal and communications theory Interpolation Motion Motion estimation Numerical Analysis, Computer-Assisted Pattern Recognition, Automated - methods Phase estimation Reproducibility of Results Robustness Sensitivity and Specificity Signal processing Signal Processing, Computer-Assisted subpixel registration Subtraction Technique Telecommunications and information theory Video compression Video Recording - methods |
| Title | Pseudopolar-based estimation of large translations, rotations, and scalings in images |
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