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http://dx.doi.org/10.7780/kjrs.2021.37.2.4

Analysis of Co-registration Performance According to Geometric Processing Level of KOMPSAT-3/3A Reference Image  

Yun, Yerin (Department of Geospatial Information, Kyungpook National University)
Kim, Taeheon (School of Convergence & Fusion System Engineering, Kyungpook National University)
Oh, Jaehong (Department of Civil Engineering, Korea Maritime and Ocean University)
Han, Youkyung (Department of Civil Engineering, Seoul National University of Science and Technology)
Publication Information
Korean Journal of Remote Sensing / v.37, no.2, 2021 , pp. 221-232 More about this Journal
Abstract
This study analyzed co-registration results according to the geometric processing level of reference image, which are Level 1R and Level 1G provided from KOMPSAT-3 and KOMPSAT-3A images. We performed co-registration using each Level 1R and Level 1G image as a reference image, and Level 1R image as a sensed image. For constructing the experimental dataset, seven Level 1R and 1G images of KOMPSAT-3 and KOMPSAT-3A acquired from Daejeon, South Korea, were used. To coarsely align the geometric position of the two images, SURF (Speeded-Up Robust Feature) and PC (Phase Correlation) methods were combined and then repeatedly applied to the overlapping region of the images. Then, we extracted tie-points using the SURF method from coarsely aligned images and performed fine co-registration through affine transformation and piecewise Linear transformation, respectively, constructed with the tie-points. As a result of the experiment, when Level 1G image was used as a reference image, a relatively large number of tie-points were extracted than Level 1R image. Also, in the case where the reference image is Level 1G image, the root mean square error of co-registration was 5 pixels less than the case of Level 1R image on average. We have shown from the experimental results that the co-registration performance can be affected by the geometric processing level related to the initial geometric relationship between the two images. Moreover, we confirmed that the better geometric quality of the reference image achieved the more stable co-registration performance.
Keywords
KOMPSAT-3.3A; Co-registration; Geometric processing level; Speeded-Up Robust Feature (SURF); Phase Correlation (PC);
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Times Cited By KSCI : 2  (Citation Analysis)
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