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Issue No. 01 - Jan. (2018 vol. 29)
ISSN: 1045-9219
pp: 16-30
Tahsin Reza , Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
Aaron Zimmer , 3vGeomatics, Vancouver, BC, Canada
Jose Manuel Delgado Blasco , Grupo de Investigación Microgeodesia Jaén, Universidad de Jaén, Jaén, Spain
Parwant Ghuman , 3vGeomatics, Vancouver, BC, Canada
Tanuj Kr Aasawat , Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
Matei Ripeanu , Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada
ABSTRACT
Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technology used for estimating the displacement of an object on the ground or the earth's surface itself. Persistent Scatterer-InSAR (PS-InSAR) is a category of time series algorithms enabling high resolution monitoring. PS-InSAR relies on successful selection of points that appear stable across a set of satellite images taken over time. This paper presents PtSel, a new algorithm for selecting these points, a problem known as Persistent Scatterer Selection. The key advantage of PtSel over the key existing techniques is that it does not require model assumptions, yet preserves solution accuracy. Motivated by the abundance of parallelism the algorithm exposes, we have implemented it for GPUs. Our evaluation using real-world data shows that the GPU implementation not only offers superior performance but also scales linearly with GPU count and workload size. We compare the GPU implementation and a parallel CPU implementation: a consumer grade GPU offers 18x speedup over a 16-core Ivy Bridge Xeon System, while four GPUs offer 65x speedup. The GPU solution consumes 28x less energy than the CPU-only solution. Additionally, we present a comparison with the most widely used PS-interferometry software package StaMPS, in terms of point selection coverage and precision.
INDEX TERMS
Graphics processing units, Coherence, Synthetic aperture radar, Image resolution, Satellites, Acceleration
CITATION

T. Reza, A. Zimmer, J. M. Blasco, P. Ghuman, T. K. Aasawat and M. Ripeanu, "Accelerating Persistent Scatterer Pixel Selection for InSAR Processing," in IEEE Transactions on Parallel & Distributed Systems, vol. 29, no. 1, pp. 16-30, 2018.
doi:10.1109/TPDS.2017.2706291
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