Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 1017-1024, 2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
30 Apr 2015
C. Theoharatos1, A. Makedonas1, N. Fragoulis1, V. Tsagaris1, and S. Costicoglou2 1Computer Vision Systems, IRIDA Labs S.A., Patras Science Park, Stadiou Str., Platani, 26504 Patras, Greece
2Space Hellas S.A., 312 Messogion Ave., 15341 Athens, Greece
Keywords: Polarimetric data fusion, 2D-PCA, vessel detection, CFAR detector, Weibull distribution, RadarSat-2, Envisat Abstract. Data fusion has lately received a lot of attention as an effective technique for several target detection and classification applications in different remote sensing areas. In this work, a novel data fusion scheme for improving the detection accuracy of ship targets in polarimetric data is proposed, based on 2D principal components analysis (2D-PCA) technique. By constructing a fused image from different polarization channels, increased performance of ship target detection is achieved having higher true positive and lower false positive detection accuracy as compared to single channel detection performance. In addition, the use of 2D-PCA provides the ability to discriminate and classify objects and regions in the resulting image representation more effectively, with the additional advantage of being more computational efficient and requiring less time to determine the corresponding eigenvectors, compared to e.g. conventional PCA. Throughout our analysis, a constant false alarm rate (CFAR) detection model is applied to characterize the background clutter and discriminate ship targets based on the Weibull distribution and the calculation of local statistical moments for estimating the order statistics of the background clutter. Appropriate pre-processing and post-processing techniques are also introduced to the process chain, in order to boost ship discrimination and suppress false alarms caused by range focusing artifacts. Experimental results provided on a set of Envisat and RadarSat-2 images (dual and quad polarized respectively), demonstrate the advantage of the proposed data fusion scheme in terms of detection accuracy as opposed to single data ship detection and conventional PCA, in various sea conditions and resolutions. Further investigation of other data fusion techniques is currently in progress.
Conference paper (PDF, 1128 KB)

Citation: Theoharatos, C., Makedonas, A., Fragoulis, N., Tsagaris, V., and Costicoglou, S.: DETECTION OF SHIP TARGETS IN POLARIMETRIC SAR DATA USING 2D-PCA DATA FUSION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 1017-1024, doi:10.5194/isprsarchives-XL-7-W3-1017-2015, 2015.

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