메뉴 건너뛰기




Volumn 10, Issue 12, 2017, Pages 1253-1269

Automatic sub-pixel co-registration of Landsat-8 Operational Land Imager and Sentinel-2A Multi-Spectral Instrument images using phase correlation and machine learning based mapping

Author keywords

Landsat 8; machine learning; misregistration; phase correlation; random forest; Sentinel 2; Sub pixel co registration

Indexed keywords

DECISION TREES; IMAGE CODING; LEARNING SYSTEMS; MACHINE LEARNING; MEAN SQUARE ERROR; PHOTOMAPPING; RANDOM FORESTS;

EID: 85015947372     PISSN: 17538947     EISSN: 17538955     Source Type: Journal    
DOI: 10.1080/17538947.2017.1304586     Document Type: Article
Times cited : (58)

References (27)
  • 3
    • 0035478854 scopus 로고    scopus 로고
    • Random Forests
    • Breiman, L., 2001. “Random Forests.” Machine Learning 45 (1): 5–32. doi:10.1023/A:1010933404324.
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 4
    • 34247644569 scopus 로고    scopus 로고
    • Automatic Panoramic Image Stitching Using Invariant Features
    • Brown, M., and D. G., Lowe. 2007. Automatic Panoramic Image Stitching Using Invariant Features.” International Journal of Computer Vision 74 (1): 59–73. doi:10.1007/s11263-006-0002-3.
    • (2007) International Journal of Computer Vision , vol.74 , Issue.1 , pp. 59-73
    • Brown, M.1    Lowe, D.G.2
  • 7
    • 85033988419 scopus 로고    scopus 로고
    • S2 MPC. Data Quality Report.” Ref: S2-PDGS-MPC-DQR, Issue: 08, Date: 05/10/2016
    • ESA. 2016a. “S2 MPC. Data Quality Report.” Ref: S2-PDGS-MPC-DQR, Issue: 08, Date: 05/10/2016. https://earth.esa.int/documents/247904/685211/Sentinel-2-Data-Quality-Report.
    • (2016)
  • 8
    • 85034003095 scopus 로고    scopus 로고
    • Sentinel-2 Products Specification Document.” Ref: S2-PDGS-TAS-DI-PSD, Issue: 14.0, Date: 15/07/2016
    • ESA. 2016b. “Sentinel-2 Products Specification Document.” Ref: S2-PDGS-TAS-DI-PSD, Issue: 14.0, Date: 15/07/2016. https://earth.esa.int/web/sentinel/user-guides/sentinel-2-msi/document-library.
    • (2016)
  • 9
    • 0019574599 scopus 로고
    • Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography
    • Fischler, M. A., and R. C., Bolles. 1981. “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography.” Communications of the ACM 24 (6): 381–395. doi:10.1145/358669.358692.
    • (1981) Communications of the ACM , vol.24 , Issue.6 , pp. 381-395
    • Fischler, M.A.1    Bolles, R.C.2
  • 10
    • 0000014486 scopus 로고
    • Cluster Analysis of Multivariate Data: Efficiency Versus Interpretability of Classifications
    • Forgy, E. W., 1965. “Cluster Analysis of Multivariate Data: Efficiency Versus Interpretability of Classifications.” Biometrics 21: 768–769.
    • (1965) Biometrics , vol.21 , pp. 768-769
    • Forgy, E.W.1
  • 11
    • 70350042683 scopus 로고    scopus 로고
    • Automated Registration and Orthorectification Package for Landsat and Landsat-Like Data Processing
    • Gao, F., J., Masek, and R. E., Wolfe. 2009. “Automated Registration and Orthorectification Package for Landsat and Landsat-Like Data Processing.” Journal of Applied Remote Sensing 3 (1): 033515–033515. doi:10.1117/1.3104620.
    • (2009) Journal of Applied Remote Sensing , vol.3 , Issue.1 , pp. 33515
    • Gao, F.1    Masek, J.2    Wolfe, R.E.3
  • 12
    • 40149088424 scopus 로고    scopus 로고
    • Efficient Subpixel Image Registration Algorithms
    • Guizar-Sicairos, M., S. T., Thurman, and J. R., Fienup. 2008. “Efficient Subpixel Image Registration Algorithms.” Optics Letters 33 (2): 156–158. doi:10.1364/OL.33.000156.
    • (2008) Optics Letters , vol.33 , Issue.2 , pp. 156-158
    • Guizar-Sicairos, M.1    Thurman, S.T.2    Fienup, J.R.3
  • 13
    • 84876345012 scopus 로고    scopus 로고
    • Assessment of the NASA–USGS Global Land Survey (GLS) Datasets
    • Gutman, G., C., Huang, G., Chander, P., Noojipady, and J. G., Masek. 2013. “Assessment of the NASA–USGS Global Land Survey (GLS) Datasets.” Remote Sensing of Environment 134: 249–265. doi:10.1016/j.rse.2013.02.026.
    • (2013) Remote Sensing of Environment , vol.134 , pp. 249-265
    • Gutman, G.1    Huang, C.2    Chander, G.3    Noojipady, P.4    Masek, J.G.5
  • 14
    • 84955258601 scopus 로고    scopus 로고
    • The Vegetation Greenness Trend in Canada and US Alaska From 1984–2012 Landsat Data
    • Ju, J., and J. G., Masek. 2016. “The Vegetation Greenness Trend in Canada and US Alaska From 1984–2012 Landsat Data.” Remote Sensing of Environment 176: 1–16. doi:10.1016/j.rse.2016.01.001.
    • (2016) Remote Sensing of Environment , vol.176 , pp. 1-16
    • Ju, J.1    Masek, J.G.2
  • 15
    • 84918576219 scopus 로고    scopus 로고
    • NASA Land Cover and Land Use Change (LCLUC): An Interdisciplinary Research Program
    • Justice, C., G., Gutman, and K. P., Vadrevu. 2015. “NASA Land Cover and Land Use Change (LCLUC): An Interdisciplinary Research Program.” Journal of Environmental Management 148: 4–9. doi:10.1016/j.jenvman.2014.12.004.
    • (2015) Journal of Environmental Management , vol.148 , pp. 4-9
    • Justice, C.1    Gutman, G.2    Vadrevu, K.P.3
  • 16
    • 84911420374 scopus 로고    scopus 로고
    • Orthorectification of Sich-2 Satellite Images Using Elastic Models
    • IEEE, and,.” In
    • Kravchenko, O., M., Lavrenyuk, and N., Kussul. 2014. “Orthorectification of Sich-2 Satellite Images Using Elastic Models.” In 2014 IEEE Geoscience and Remote Sensing Symposium, 2281–2284. IEEE. doi:10.1109/IGARSS.2014.6946925.
    • (2014) 2014 IEEE Geoscience and Remote Sensing Symposium , pp. 2281-2284
    • Kravchenko, O.1    Lavrenyuk, M.2    Kussul, N.3
  • 18
    • 0020102027 scopus 로고
    • Least Squares Quantization in PCM
    • Lloyd, S., 1982. “Least Squares Quantization in PCM.” IEEE Transactions on Information Theory 28 (2): 129–137. doi:10.1109/TIT.1982.1056489.
    • (1982) IEEE Transactions on Information Theory , vol.28 , Issue.2 , pp. 129-137
    • Lloyd, S.1
  • 21
    • 85019930085 scopus 로고    scopus 로고
    • Exploring Google Earth Engine Platform for Big Data Processing: Classification of Multi-Temporal Satellite Imagery for Crop Mapping
    • Shelestov, A., M., Lavreniuk, N., Kussul, A., Novikov, and S., Skakun. 2017. “Exploring Google Earth Engine Platform for Big Data Processing: Classification of Multi-Temporal Satellite Imagery for Crop Mapping.” Frontiers in Earth Science 5 (17): 1–7. doi:10.3389/feart.2017.00017.
    • (2017) Frontiers in Earth Science , vol.5 , Issue.17 , pp. 1-7
    • Shelestov, A.1    Lavreniuk, M.2    Kussul, N.3    Novikov, A.4    Skakun, S.5
  • 22
    • 84938815954 scopus 로고    scopus 로고
    • Efficiency Assessment of Multitemporal C-Band Radarsat-2 Intensity and Landsat-8 Surface Reflectance Satellite Imagery for Crop Classification in Ukraine
    • Skakun, S., N., Kussul, A. Y., Shelestov, M., Lavreniuk, and O., Kussul. 2016. “Efficiency Assessment of Multitemporal C-Band Radarsat-2 Intensity and Landsat-8 Surface Reflectance Satellite Imagery for Crop Classification in Ukraine.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9 (8): 3712–3719. doi:10.1109/JSTARS.2015.2454297.
    • (2016) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol.9 , Issue.8 , pp. 3712-3719
    • Skakun, S.1    Kussul, N.2    Shelestov, A.Y.3    Lavreniuk, M.4    Kussul, O.5
  • 23
    • 84912142286 scopus 로고    scopus 로고
    • Landsat 8 Operational Land Imager on-Orbit Geometric Calibration and Performance
    • Storey, J., M., Choate, and K., Lee. 2014. “Landsat 8 Operational Land Imager on-Orbit Geometric Calibration and Performance.” Remote Sensing 6 (11): 11127–11152. doi:10.3390/rs61111127.
    • (2014) Remote Sensing , vol.6 , Issue.11 , pp. 11127-11152
    • Storey, J.1    Choate, M.2    Lee, K.3
  • 24
    • 84982293141 scopus 로고    scopus 로고
    • A Note on the Temporary Misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery
    • Storey, J., D. P., Roy, J., Masek, F., Gascon, J., Dwyer, and M., Choate. 2016. “A Note on the Temporary Misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery.” Remote Sensing of Environment 186: 121–122. doi:10.1016/j.rse.2016.08.025.
    • (2016) Remote Sensing of Environment , vol.186 , pp. 121-122
    • Storey, J.1    Roy, D.P.2    Masek, J.3    Gascon, F.4    Dwyer, J.5    Choate, M.6
  • 25
    • 84964645155 scopus 로고    scopus 로고
    • Preliminary Analysis of the Performance of the Landsat 8/OLI Land Surface Reflectance Product
    • Vermote, E., C., Justice, M., Claverie, and B., Franch. 2016. “Preliminary Analysis of the Performance of the Landsat 8/OLI Land Surface Reflectance Product.” Remote Sensing of Environment 185: 46–56. doi:10.1016/j.rse.2016.04.008.
    • (2016) Remote Sensing of Environment , vol.185 , pp. 46-56
    • Vermote, E.1    Justice, C.2    Claverie, M.3    Franch, B.4
  • 26
    • 84982278329 scopus 로고    scopus 로고
    • An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery
    • Yan, L., D. P., Roy, H., Zhang, J., Li, and H., Huang. 2016. “An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery.” Remote Sensing 8 (6): 520. doi:10.3390/rs8060520.
    • (2016) Remote Sensing , vol.8 , Issue.6 , pp. 520
    • Yan, L.1    Roy, D.P.2    Zhang, H.3    Li, J.4    Huang, H.5
  • 27
    • 0043237770 scopus 로고    scopus 로고
    • Image Registration Methods: A Survey
    • Zitova, B., and J., Flusser. 2003. “Image Registration Methods: A Survey.” Image and Vision Computing 21 (11): 977–1000. doi:10.1016/S0262-8856(03)00137-9.
    • (2003) Image and Vision Computing , vol.21 , Issue.11 , pp. 977-1000
    • Zitova, B.1    Flusser, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.