Automatic Registration between High Resolution SAR Image and GIS Road Network Based on Pairwise Constraint and ICM Optimization

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Abstract:

Synthetic aperture radar (SAR) technique has been widely applied in disaster monitoring and evaluation, because of its all-weather and all-time capability. In particular, the integration of high resolution SAR image and GIS data has been proved to be an effective solution to change detection for rapid disaster response. However, accurate registration of SAR image and GIS data remains a challenging task. On the one hand, SAR image and GIS data are two different representation levels of the real world. GIS data lacks of grey value and texture information, thus traditional use of grey-based and texture-based feature descriptors for feature matching in GIS data is impossible. On the other hand, the extraction of matching primitives is difficult in the SAR image due to the speckle noise. Moreover, though features can be extracted in the SAR image, the matching can be difficult since features may be fractured and missing. In this paper, we propose a new method for vector-to-SAR image registration which utilizes conjugate line-pair intersections as matching primitives. The core idea consists in two aspects: 1) Different from traditional road intersection based registration methods, conjugate line-pair intersections are employed as matching primitive in the proposed method. 2) To find out the optimal set of matching features, a matching technique that using pairwise constraint and the iterative conditional mode (ICM) optimization algorithm is introduced. Experiment results proved the reliability and feasibility of the proposed method.

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Advanced Materials Research (Volumes 989-994)

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3639-3643

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July 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Li Xin-wu and so on. A new approach to collapsed building extraction using Radarsat-2 polarimetric SAR imagery [J]. IEEE Transactions and Remote Sensing Letters, 2012, 9(4): 677-681.

DOI: 10.1109/lgrs.2011.2178392

Google Scholar

[2] Li De-ren. Remotely sensed images and GIS data fusion for automatic change detection [J]. International Journal of Image and Data Fusion, 2010, 1(1): 99-108.

DOI: 10.1080/19479830903562074

Google Scholar

[3] Song Wen-bo and so on. Automated geospatial conflation of vector road maps to high resolution imagery [J]. IEEE Transactions on Image Processing, 2009, 18(2): 388-400.

DOI: 10.1109/tip.2008.2008044

Google Scholar

[4] Liu Zhi-qing and so on. Automatic registration between remote sensing image and vector data based on line features [J]. 19th International Conference on Geoinformatics, 2011: 1-5.

DOI: 10.1109/geoinformatics.2011.5981167

Google Scholar

[5] Wang Cai-xia and so on. Image-to-X registration using linear features [J]. IEEE International Fuzzy Systems Conference, 2007: 1-7.

Google Scholar

[6] Chen Min and so on. Robust affine-invariant line matching for high resolution remote sensing images [J]. Photogrammetric Engineering & Remote Sensing, 2013, 79(8): 753-760.

DOI: 10.14358/pers.79.8.753

Google Scholar

[7] Wang Zhi-heng and so on. MSLD: a robust descriptor for line matching [J]. Pattern Recognition, 2009 (42): 941-953.

DOI: 10.1016/j.patcog.2008.08.035

Google Scholar

[8] Izadi M. and Saeedi P. Robust weighted graph transformation matching for rigid and nonrigid image registration [J]. IEEE Transactions on Image Processing, 2012, 21(10): 4369-4382.

DOI: 10.1109/tip.2012.2208980

Google Scholar

[9] Liu Junyi and so on. Road extraction from SAR imagery based on an improved particle filtering and snake model [J]. International Journal of Remote Sensing, 2013, 34(22): 8199-8214.

DOI: 10.1080/01431161.2013.835082

Google Scholar

[10] Long Teng-fei and so on. Automatic line segment registration using Gaussian Mixture Model and Expectation-Maximization algorithm [J]. IEEE Journal of Selected Topics In Applied Earth Observation and Remote Sensing, 2013: 1-12.

DOI: 10.1109/jstars.2013.2273871

Google Scholar