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http://dx.doi.org/10.7319/kogsis.2015.23.1.081

Matching Points Extraction Between Optical and TIR Images by Using SURF and Local Phase Correlation  

Han, You Kyung (Fondazione Bruno Kessler)
Choi, Jae Wan (School of Civil Engineering, Chungbuk National University)
Publication Information
Journal of Korean Society for Geospatial Information Science / v.23, no.1, 2015 , pp. 81-88 More about this Journal
Abstract
Various satellite sensors having ranges of the visible, infrared, and thermal wavelengths have been launched due to the improvement of hardware technologies of satellite sensors development. According to the development of satellite sensors with various wavelength ranges, the fusion and integration of multisensor images are proceeded. Image matching process is an essential step for the application of multisensor images. Some algorithms, such as SIFT and SURF, have been proposed to co-register satellite images. However, when the existing algorithms are applied to extract matching points between optical and thermal images, high accuracy of co-registration might not be guaranteed because these images have difference spectral and spatial characteristics. In this paper, location of control points in a reference image is extracted by SURF, and then, location of their corresponding pairs is estimated from the correlation of the local similarity. In the case of local similarity, phase correlation method, which is based on fourier transformation, is applied. In the experiments by simulated, Landsat-8, and ASTER datasets, the proposed algorithm could extract reliable matching points compared to the existing SURF-based method.
Keywords
Matching Points; Image Registration; SURF; Local Phase Correlation; Optical Image; TIR Image;
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Times Cited By KSCI : 3  (Citation Analysis)
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1 Bay, H., Ess, A., Tuytelaars, T. and Gool, L. V., 2008, Speeded-up robust features, Computer Vision and Image Understanding, Vol. 110, No. 3, pp. 346-359.   DOI
2 Byun, Y., Choi, J. and Han, Y., 2013, An area-based image fusion scheme for the integration of SAR and optical satellite imagery, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 6, No. 5, pp. 2212-2220.   DOI
3 Dong, J., Zhuang, D., Huang Y. and Fu, J., 2009, Advances in multi-sensor data fusion: algorithms and applications, Sensors, Vol. 9, No. 10, pp. 7771-7784.   DOI   ScienceOn
4 Fischler, M. and Bolles, R., 1981, Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, Vol. 24, No. 6, pp. 381-395.   DOI
5 Gwon, H., Lee, I. and Choi, T., 2013, Electro-optics and infrared image registration using gaussian pyramids, Advanced Science and Technology Letters, Vol. 29(SIP 2013), pp. 55-59.
6 Han, Y., Byun, Y., Choi, J., Han, D. and Kim, Y., 2012, Automatic registration of high-resolution images using local properties of features, Photogrammetric Engineering and Remote Sensing, Vol. 78, No. 3, pp. 211-221.   DOI   ScienceOn
7 Han, Y., Choi, J., Byun, Y. and Kim, Y., 2014, Parameter optimization for the extraction of matching points between high-resolution multisensor images, IEEE Transactions on Geoscience and Remote Sensing, Vol. 52, No. 9, pp. 5612-5621.   DOI
8 Klimaszewski, J., Kondej, M., Kawecki, M. and Putz, B., 2013, Registration of Infrared and visible images based on edge extraction and phase correlation approaches, Image Processing and Communications Challenges 4, Vol. 184, pp. 153-162.   DOI
9 Lee, Y., 2014, Automatic extraction method of control point based on geospatial web service, Journal of the Korean Society for Geospatial Information System, Vol. 22, No. 2, pp. 17-24.   DOI
10 Lowe, D., 2004, Distinctive image features from scale-invariant keypoints, International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110.   DOI
11 Lu, P., 2013, Rotation invariant Registration of 2D aerial images using local phase correlation, Master thesis, Uppsala University.
12 Ye, C., 2014, Image registration using outlier removal and triangulation-based local transformation, Korean Journal of Remote Sensing, Vol. 30, No. 6, pp. 787-795.   DOI
13 Yeom, J., Han, Y. and Kim, Y., 2013, Analysis of shadow effect on high resolution satellite image matching in urban area, Journal of the Korean Society for Geospatial Information System, Vol. 21, No. 2, pp. 93-98.   DOI
14 Zhao, D., Yang, Y., Ji, Z. and Hu, X., 2014, Rapid multimodality registration based on MM-SURF, Neurocomputing, Vol. 131, pp. 87-97.   DOI