Research Papers

Fast geocoding of spaceborne synthetic-aperture radar images using graphics processing units

[+] Author Affiliations
Timo Balz

Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, Hubei 430079 China

Lu Zhang

Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, Hubei 430079 China

Mingsheng Liao

Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, Hubei 430079 China

J. Appl. Remote Sens. 6(1), 063553 (Jul 16, 2012). doi:10.1117/1.JRS.6.063553
History: Received December 7, 2011; Revised May 17, 2012; Accepted June 7, 2012
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Abstract.  Geocoding is crucial for using remotely sensed data in almost all applications, especially when a combination of multiple data sources is required. However, geocoding a synthetic-aperture radar image with the standard range-Doppler method is a time-consuming process due to unavoidable iterations. Using a replacement sensor model, for example the rational polynomial camera (RPC) model, can significantly reduce the calculation time cost. Another way to improve the calculation efficiency is to use massively parallel processing techniques. Modern graphics processing units (GPU) can be used as parallel processing units for computationally intensive applications. Using NVIDIA's Compute Unified Device Architecture (CUDA) the implementation of the range-Doppler and RPC methods on GPUs is easy, because the existing C/C++ code can be reused. With further optimizations for GPU processing, tremendous improvements can be achieved. The CUDA implementations run about 10 to 30 times faster compared with similar implementations on the central processing unit (CPU), and almost 200 times faster if particularly optimized for GPU computing.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Timo Balz ; Lu Zhang and Mingsheng Liao
"Fast geocoding of spaceborne synthetic-aperture radar images using graphics processing units", J. Appl. Remote Sens. 6(1), 063553 (Jul 16, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063553


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