A WTLS-based method for remote sensing imagery registration
This paper introduces a weighted total least squares (WTLS)-based estimator into image registration to deal with the coordinates of control points (CPs) that are of unequal accuracy. The performance of the estimator is investigated by means of simulation experiments using different coordinate errors...
| Main Authors: | , , , , , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
2015
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/77047 |
| _version_ | 1848763806937776128 |
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| author | Wu, T. Ge, Y. Wang, J. Stein, A. Song, Yongze Du, Y. Ma, J. |
| author_facet | Wu, T. Ge, Y. Wang, J. Stein, A. Song, Yongze Du, Y. Ma, J. |
| author_sort | Wu, T. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper introduces a weighted total least squares (WTLS)-based estimator into image registration to deal with the coordinates of control points (CPs) that are of unequal accuracy. The performance of the estimator is investigated by means of simulation experiments using different coordinate errors. Comparisons with ordinary least squares (LS), total LS (TLS), scaled TLS, and weighted LS estimators are made. A novel adaptive weight determination scheme is applied to experiments with remotely sensed images. These illustrate the practicability and effectiveness of the proposed registration method by collecting CPs with different-sized errors from multiple reference images with different spatial resolutions. This paper concludes that the WTLS-based iteratively reweighted TLS method achieves a more robust estimation of model parameters and higher registration accuracy if heteroscedastic errors occur in both the coordinates of reference CPs and target CPs. © 2014 IEEE. |
| first_indexed | 2025-11-14T11:09:19Z |
| format | Journal Article |
| id | curtin-20.500.11937-77047 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:09:19Z |
| publishDate | 2015 |
| publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-770472019-12-03T01:18:43Z A WTLS-based method for remote sensing imagery registration Wu, T. Ge, Y. Wang, J. Stein, A. Song, Yongze Du, Y. Ma, J. Science & Technology Physical Sciences Technology Geochemistry & Geophysics Engineering, Electrical & Electronic Remote Sensing Imaging Science & Photographic Technology Engineering Adaptive weight scheme image registration unequal accuracy weighted total least squares (WTLS) TOTAL-LEAST-SQUARES RANDOM SAMPLE CONSENSUS ROBUST REGRESSION SENSED IMAGERY CONTROL POINTS ESTIMATOR MODELS ERROR This paper introduces a weighted total least squares (WTLS)-based estimator into image registration to deal with the coordinates of control points (CPs) that are of unequal accuracy. The performance of the estimator is investigated by means of simulation experiments using different coordinate errors. Comparisons with ordinary least squares (LS), total LS (TLS), scaled TLS, and weighted LS estimators are made. A novel adaptive weight determination scheme is applied to experiments with remotely sensed images. These illustrate the practicability and effectiveness of the proposed registration method by collecting CPs with different-sized errors from multiple reference images with different spatial resolutions. This paper concludes that the WTLS-based iteratively reweighted TLS method achieves a more robust estimation of model parameters and higher registration accuracy if heteroscedastic errors occur in both the coordinates of reference CPs and target CPs. © 2014 IEEE. 2015 Journal Article http://hdl.handle.net/20.500.11937/77047 10.1109/TGRS.2014.2318705 English IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC restricted |
| spellingShingle | Science & Technology Physical Sciences Technology Geochemistry & Geophysics Engineering, Electrical & Electronic Remote Sensing Imaging Science & Photographic Technology Engineering Adaptive weight scheme image registration unequal accuracy weighted total least squares (WTLS) TOTAL-LEAST-SQUARES RANDOM SAMPLE CONSENSUS ROBUST REGRESSION SENSED IMAGERY CONTROL POINTS ESTIMATOR MODELS ERROR Wu, T. Ge, Y. Wang, J. Stein, A. Song, Yongze Du, Y. Ma, J. A WTLS-based method for remote sensing imagery registration |
| title | A WTLS-based method for remote sensing imagery registration |
| title_full | A WTLS-based method for remote sensing imagery registration |
| title_fullStr | A WTLS-based method for remote sensing imagery registration |
| title_full_unstemmed | A WTLS-based method for remote sensing imagery registration |
| title_short | A WTLS-based method for remote sensing imagery registration |
| title_sort | wtls-based method for remote sensing imagery registration |
| topic | Science & Technology Physical Sciences Technology Geochemistry & Geophysics Engineering, Electrical & Electronic Remote Sensing Imaging Science & Photographic Technology Engineering Adaptive weight scheme image registration unequal accuracy weighted total least squares (WTLS) TOTAL-LEAST-SQUARES RANDOM SAMPLE CONSENSUS ROBUST REGRESSION SENSED IMAGERY CONTROL POINTS ESTIMATOR MODELS ERROR |
| url | http://hdl.handle.net/20.500.11937/77047 |