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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 39, Iss. 5 — Feb. 10, 2000
  • pp: 835–849

Focal-plane processing architectures for real-time hyperspectral image processing

Sek M. Chai, Antonio Gentile, Wilfredo E. Lugo-Beauchamp, Javier Fonseca, José L. Cruz-Rivera, and D. Scott Wills  »View Author Affiliations


Applied Optics, Vol. 39, Issue 5, pp. 835-849 (2000)
http://dx.doi.org/10.1364/AO.39.000835


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Abstract

Real-time image processing requires high computational and I/O throughputs obtained by use of optoelectronic system solutions. A novel architecture that uses focal-plane optoelectronic-area I/O with a fine-grain, low-memory, single-instruction–multiple-data (SIMD) processor array is presented as an efficient computational solution for real-time hyperspectral image processing. The architecture is evaluated by use of realistic workloads to determine data throughputs, processing demands, and storage requirements. We show that traditional store-and-process system performance is inadequate for this application domain, whereas the focal-plane SIMD architecture is capable of supporting real-time performances with sustained operation throughputs of 500–1500 gigaoperations/s. The focal-plane architecture exploits the direct coupling between sensor and parallel-processor arrays to alleviate data-bandwidth requirements, allowing computation to be performed in a stream-parallel computation model, while data arrive from the sensors.

© 2000 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(100.2000) Image processing : Digital image processing
(100.2550) Image processing : Focal-plane-array image processors
(110.0110) Imaging systems : Imaging systems

History
Original Manuscript: May 18, 1999
Revised Manuscript: September 7, 1999
Published: February 10, 2000

Citation
Sek M. Chai, Antonio Gentile, Wilfredo E. Lugo-Beauchamp, Javier Fonseca, José L. Cruz-Rivera, and D. Scott Wills, "Focal-plane processing architectures for real-time hyperspectral image processing," Appl. Opt. 39, 835-849 (2000)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-39-5-835


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References

  1. M. Arias-Estrada, M. Tremblay, D. Poussart, “A focal plane architecture for motion computation,” Real-Time Imag. 2, 351–360 (1996). [CrossRef]
  2. W. C. Fang, T. Shaw, J. Yu, Y. T. Tsai, L. J. D’Luna, P. P. K. Lee, “VLSI focal-plane array processor for morphological image processing,” in Proceedings of the Fifth Annual IEEE International ASIC Conference and Exhibit (Institute of Electrical and Electronics Engineers, New York, 1992), pp. 423–426. [CrossRef]
  3. D. Poussart, M. Tremblay, A. Djemouiai, “VLSI implementation of focal plane processing for smart vision sensing,” in Pattern Recognition: Architectures, Algorithms, and Applications, R. Plamondon, H. Cheng, eds. (World Scientific, Singapore, 1991), pp. 5–23.
  4. H. Urey, W. T. Rhodes, S. P. DeWeerth, T. J. Drabik, “Optoelectronic image processor for multiresolution Gabor filtering,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (Institute of Electrical and Electronics Engineers, New York, 1996), Vol. 6, pp. 3236–3239.
  5. D. S. Wills, J. M. Baker, H. H. Cat, S. M. Chai, L. Codrescu, J. Cruz-Rivera, J. C. Eble, A. Gentile, M. A. Hopper, W. S. Lacy, A. López-Lagunas, P. May, S. Smith, T. Taha, “Processing architecture for smart pixel systems,” IEEE J. Select. Top. Quantum Electron. 2, 24–34 (1996). [CrossRef]
  6. R. Holasek, F. Protigal, G. Mooradian, M. Voelker, D. Even, M. Fene, P. Owensby, D. Breitwieser, “HIS mapping of marine and coastal environments using the Advanced Airborne Hyperspectral Imaging System (AAHIS),” in Algorithms for Multispectral and Hyperspectral Imagery III, A. Iverson, S. S. Shen, eds., Proc. SPIE3071, 169–180 (1997). [CrossRef]
  7. M. K. Hamilton, S. H. Pilorz, C. O. Davis, J. M. van den Bosch, W. J. Rhea, “Analysis of high spectral resolution coastal ocean imagery: statistical, empirical, and analytical investigation,” in Algorithms for Multispectral and Hyperspectral Imagery, A. Iverson, ed., Proc. SPIE2231, 116–126 (1994). [CrossRef]
  8. M. A. Shaikh, B. Tian, M. R. Azimi-Sadjadi, K. E. Eis, T. H. VonderHaar, “An automatic neural network-based cloud detection–classification scheme using multispectral and textural features,” in Algorithms for Multispectral and Hyperspectral Imagery II, D. K. Lynch, E. P. Shettle, eds., Proc. SPIE2578, 51–61 (1996). [CrossRef]
  9. A. F. Hayden, R. J. Noll, “Remote trace-gas quantification using thermal IR spectroscopy and digital filtering based on principal components of background scene clutter,” in Algorithms for Multispectral and Hyperspectral Imagery III, A. Iverson, S. S. Shen, eds., Proc. SPIE3071, 158–168 (1997). [CrossRef]
  10. P. H. Swain, S. M. Davis, Remote Sensing: The Quantitative Approach (McGraw-Hill, New York, 1978), pp. 55–62.
  11. J. Schott, Remote Sensing: The Image Chain Approach (Oxford U. Press, New York, 1997), pp. 125–188.
  12. R. J. Birk, T. B. McCord, “Airborne hyperspectral sensor systems,” IEEE Aerospace Electron. Sys. 9 (10), 26–33 (1994).
  13. P. Song, “Direct RDRAM sustains 1.5 Gbytes/s,” (MicroDesign Resources, 874 Gravenstein Highway South, Sebastopol, Calif. 95472, 27October1997).
  14. E. S. Eid, E. Fossum, “Real-time focal-plane array image processor,” in Automated Inspection and High-Speed Vision Architectures III (International Society for Optical Engineering, Philadelphia, Pa., 1989), pp. 2–12.
  15. MasPar MP-2 Users Guide, Version A5 (MasPar Corporation, 749 North Mary Avenue, Sunnyvale, Calif. 94086, 1994).
  16. MasPar MP-2 System Data Sheet (MasPar Corporation, 749 North Mary Avenue, Sunnyvale, Calif. 94086, 1993).
  17. J. Adams, K. Parulski, K. Spaulding, “Color processing in digital cameras,” IEEE Micro. 18, 20–30 (1998). [CrossRef]
  18. K. A. Parulski, “Color filter arrays and processing alternatives for one-chip cameras,” IEEE Trans. Electron. Devices ED-32, 1381–1389 (1985). [CrossRef]
  19. H. J. Lee, J. C. Liu, A. K. Chan, C. K. Chui, “Parallel implementation of wavelet decomposition–reconstruction algorithms,” in Wavelet Applications, H. H. Szu, ed., Proc. SPIE2242, 248–259 (1994). [CrossRef]
  20. A. Gentile, H. H. Cat, F. Kossentini, F. Sorbello, D. S. Wills, “Real-time vector quantization-based image compression on the SIMPil low-memory SIMD architecture,” in Proceedings of the 1997 International Performance, Computing, and Communications Conference (IPCCC’97) (Institute of Electrical and Electronics Engineers, New York, 1997), pp. 10–16. [CrossRef]
  21. H. J. Lee, J. C. Liu, A. K. Chan, C. K. Chui, “A parallel vector quantization algorithm for single-instruction–multiple-data (SIMD) multiprocessor systems,” in Proceedings of the Fifth IEEE Data Compression Conference (Institute of Electrical and Electronics Engineers, New York, 1995), p. 479.
  22. M. Manohar, J. C. Tilton, “Progressive vector quantization of multispectral image data using a massively parallel SIMD machine,” in Proceedings of the Second IEEE Data Compression Conference (Institute of Electrical and Electronics Engineers, New York, 1992), pp. 181–186.
  23. W. D. Hillis, The Connection Machine (MIT Press, Cambridge, Mass., 1985).
  24. Connection Machine Model CM-2 Technical Summary, Version 5.1 (Thinking Machine Corporation, 16 New England Executive Park, Burlington, Mass. 01803, 1989).
  25. H. H. Cat, A. Gentile, J. C. Eble, M. E. Lee, O. Vendier, Y. J. Joo, D. S. Wills, M. Brooke, N. M. Jokerst, A. S. Brown, “SIMPil: an OE integrated SIMD architecture for focal plane processing applications,” in Proceedings of the Third IEEE International Conference on Massively Parallel Processing Using Optical Interconnection (MMPOI-96) (Institute of Electrical and Electronics Engineers, New York, 1996), pp. 44–52. [CrossRef]
  26. S. M. Chai, A. Gentile, D. S. Wills, “Impact of power density limitation in gigascale integration for the SIMD pixel processor,” in Proceedings of the Twentieth Anniversary Conference on Advanced Research in VLSI (IEEE Computer Society, Los Alamitos, Calif., 1999), pp. 57–71. [CrossRef]
  27. A. Gentile, J. Cruz-Rivera, D. S. Wills, L. Bustelo, J. J. Figueroa, J. E. Fonseca-Camacho, W. E. Lugo-Beauchamp, R. Olivieri, M. Quiñones-Cerpa, A. H. Rivera-Ríos, I. Vargas-Gonzáles, M. Viera-Vera, “Real-time image processing on a focal plane SIMD array,” in Parallel and Distributed Processing, Vol. 1586 of Lecture Notes in Computer Science (Springer-Verlag, New York, 1999), pp. 400–405. [CrossRef]
  28. The National Technology Roadmap for Semiconductors (Semiconductor Industry Association, 181 Metro Drive, San Jose, Calif. 95110, and SEMATECH, 2706 Montopolis Drive, Austin, Tex. 78741, 1997).
  29. E. Gose, R. Johnsonbaugh, S. Jost, Pattern Recognition and Image Analysis (Prentice-Hall, Englewood Cliffs, N.J., 1996), Chap. 5.
  30. R. A. Scowengerdt, Remote Sensing: Models and Methods for Image Processing, 2nd ed. (Academic, New York, 1997), pp. 403–410.
  31. A. Gersho, R. M. Gray, Vector Quantization and Signal Compression (Kluwer Academic, Dordrecht, The Netherlands, 1992). [CrossRef]
  32. See the PICA (portable image computation architecture) research group’s SIMPil (SIMD pixel processor) home page at http://www.ee.gatech.edu/research/pica/simpil .
  33. K. Diefendorff, R. Dubey, “How multimedia workloads will change processor design,” IEEE Comput. 30, 43–45 (1997). [CrossRef]

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