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Convex regularization-based hardware/software co-design for real-time enhancement of remote sensing imagery

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Abstract

In this paper, we address a new approach for high-resolution reconstruction and enhancement of remote sensing (RS) imagery in near-real computational time based on the aggregated hardware/software (HW/SW) co-design paradigm. The software design is aimed at the algorithmic-level decrease of the computational load of the large-scale RS image enhancement tasks via incorporating into the fixed-point iterative reconstruction/enhancement procedures the convex convergence enforcement regularization by constructing the proper projectors onto convex sets (POCS) in the solution domain. The established POCS-regularized iterative techniques are performed separately along the range and azimuth directions over the RS scene frame making an optimal use of the sparseness properties of the employed sensor system modulation format. The hardware design is oriented on employing the Xilinx Field Programmable Gate Array XC4VSX35-10ff668 and performing the image enhancement/reconstruction tasks in a computationally efficient parallel fashion that meets the near-real time imaging system requirements. Finally, we report some simulation results and discuss the implementation performance issues related to enhancement of the real-world RS imagery indicative of the significantly increased performance efficiency gained with the developed approach.

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References

  1. Greco, J., Cieslewski, G., Jacobs, A., Troxel, I.A., George, A.D.: Hardware/software interface for high-performance space computing with FPGA coprocessors. IEEE Aerospace Conference, pp. 10–25 (2006)

  2. Liu, Z., Chen, S.: A parallel image processing system for SAR. In: Proceedings of Radio Science Conference Asia-Pacific, pp. 273–274 (2004)

  3. Tsai, G.R., Lin, M.C.: FPGA-based reconfigurable measurement instruments with functionality defined by user. EURASIP J. Appl. Signal Process. 206, 1–14 (2006). doi:10.1155/ASP/2006/84340

  4. Wehner, D.R.: High-Resolution Radar, 2nd edn. Artech House, Boston (1994)

    Google Scholar 

  5. Henderson, F.M.: Lewis, A.V.: Principles and applications of imaging radar. In: Manual of Remote Sensing, 3rd edn. Wiley, New York (1998)

    Google Scholar 

  6. Meyer Baese, U.: Digital Signal Processing with Field Programmable Gate Array. Springer, Berlin (2001)

    Google Scholar 

  7. Shkvarko, Y.V.: Unifying regularization and Bayesian estimation methods for enhanced imaging with remotely sensed data. Part I—Theory. IEEE Trans. Geosci. Rem. Sens. 42, 923–931 (2004). doi:10.1109/TGRS.2003.823281

    Article  Google Scholar 

  8. Shkvarko, Y.V.: Unifying regularization and bayesian estimation methods for enhanced imaging with remotely sensed data. Part II—implementation and performance issues. IEEE Trans. Geosci. Rem. Sens. 42, 932–940 (2004). doi:10.1109/TGRS.2003.823279

    Article  Google Scholar 

  9. Shkvarko, Y.V.: From matched spatial filtering towards the fused statistical descriptive regularization method for enhanced radar imaging. EURASIP J. Appl. Signal Process. 2006, 1–9 (2006). doi:10.1155/ASP/2006/39657

    Google Scholar 

  10. Ponomaryov, V.I.: Real-time 2D–3D filtering using order statistics based algorithms. J. Real-Time Image Process. 1, 173–194 (2007). doi:10.1007/s11554-007-0021-5

    Article  Google Scholar 

  11. PlanAhead tutorial, release 10.1. Xilinx. http://www.xilinx.com

  12. EDK 9.1 MicroBlaze tutorial in Virtex-4, Xilinx. http://www.xilinx.com

  13. Shkvarko, Y.V., Perez Meana, H.M., Castillo Atoche, A.: Enhanced radar imaging in uncertain environment: a descriptive experiment design regularization paradigm, Int. J. Navig. Obs., 2008, 11 (2008)

  14. Space Imaging. http://www.spaceimaging.com/quicklook. GeoEye Inc. (2008)

  15. Marquardt, A., Betz, V., Rose, J.: Speed and area tradeoffs in cluster-based FPGA architectures. IEEE Trans. Very Large Scale Integr. Syst. 8(1), 84–93 (2000)

    Article  Google Scholar 

  16. Navabi, Z.: Embedded Core Design with FPGAs. McGraw-Hill Professional, NY (2006)

  17. Guardino, C., Riviera, Y., Goodman, J., Riviera, W.: Parallel implementation of an inversion model for hyperspectral remote sensing. In: 49th IEEE Midwest Symposium on Circuit and Systems (MWSCAS) (2006)

  18. Thunderhead System. http://thunderhead.gsfc.nasa.gov/

  19. Plaza, A., Benediktsson, J.A., Broadman, J., Brazile, J.: Recent advances in techniques for hyperspectral image processing. J. Remote Sens. Environ. (2009, accepted)

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Authors and Affiliations

  1. CINVESTAV del IPN, Unidad Guadalajara, Avenida Científica #1145, Colonia El Bajío, CP 45015, Zapopan, Jalisco, Mexico

    Alejandro Castillo Atoche & D. Torres Roman

  2. Universidad Autónoma de Yucatán, Av. Industrias No Contaminantes s/n, Apdo. Postal 150, Mérida, Yucatán, Mexico

    Alejandro Castillo Atoche

  3. ESIME del IPN, Unidad Culhuacan, Av. Santa Ana #1000, Col. San Fco. Culhuacan, Del. Coyoacan, Mexico DF, Mexico

    Y. Shkvarko & H. Perez Meana

Authors
  1. Alejandro Castillo Atoche
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  2. Y. Shkvarko
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  3. D. Torres Roman
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  4. H. Perez Meana
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Correspondence to Alejandro Castillo Atoche.

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Castillo Atoche, A., Shkvarko, Y., Torres Roman, D. et al. Convex regularization-based hardware/software co-design for real-time enhancement of remote sensing imagery. J Real-Time Image Proc 4, 261–272 (2009). https://doi.org/10.1007/s11554-009-0115-3

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  • DOI: https://doi.org/10.1007/s11554-009-0115-3

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