Abstract
A novel hybrid co-design for implementing high-resolution reconstruction algorithms, for near real time implementation of remote sensing (RS) imagery, is addressed in this paper. In the proposed co-design scheme, the inverse square root and the matrix operations of the robust adaptive space filter algorithm are implemented as accelerators units in a Field Programmable Gate Array (FPGA) using piecewise polynomial approximations and systolic array (SA) techniques. Then, the FPGA based accelerator is integrated with an ARM processor in a HW/SW co-design paradigm that meets the (near) real time imaging systems requirements in spite of conventional computations. Finally, we report and discuss the results of the hybrid FPGA/ARM co-design implementation in a Xilinx Virtex-5 XC5VFX70TFFG1136 for reconstruction of real world RS images.
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Shkvarko, Y.V.: Unifying Regularization and Bayesian Estimation Methods for Enhanced Imaging with Remotely Sensed Data. Part I Theory. IEEE Transactions on Geoscience and Remote Sensing 42, 923–931 (2004)
Wehner, D.R.: High-Resolution Radar, 2nd edn. Artech House, Boston (1994)
Castillo Atoche, A., Torres, D., Shkvarko, Y.V.: Towards Real Time Implementation of Reconstructive Signal Processing Algorithms Using Systolic Arrays Coprocessors. Journal of Systems Architecture 56(8), 327–339 (2010b)
Kung, S.Y.: VLSI Array Processors. Prentice-Hall, NY (1998)
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Góngora-Martín, C., Castillo-Atoche, A., Estrada-López, J., Vázquez-Castillo, J., Ortegón-Aguilar, J., Carrasco-Álvarez, R. (2014). Hybrid FPGA/ARM Co-design for Near Real Time of Remote Sensing Imagery. In: Bayro-Corrochano, E., Hancock, E. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2014. Lecture Notes in Computer Science, vol 8827. Springer, Cham. https://doi.org/10.1007/978-3-319-12568-8_126
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DOI: https://doi.org/10.1007/978-3-319-12568-8_126
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12567-1
Online ISBN: 978-3-319-12568-8
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