Co-design of software and hardware to implement remote sensing algorithms

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Both for offline searches through large data archives and for onboard computation at the sensor head, there is a growing need for ever-more rapid processing of remote sensing data. For many algorithms of use in remote sensing, the bulk of the processing takes place in an 'inner loop' with a large number of simple operations. For these algorithms, dramatic speedups can often be obtained with specialized hardware. The difficulty and expense of digital design continues to limit applicability of this approach, but the development of new design tools is making this approach more feasible, and some notable successes have been ... continued below

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8 p.

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Theiler, J. P. (James P.); Frigo, J. (Janette); Gokhale, M. (Maya) & Szymanski, J. J. (John J.) January 1, 2001.

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Description

Both for offline searches through large data archives and for onboard computation at the sensor head, there is a growing need for ever-more rapid processing of remote sensing data. For many algorithms of use in remote sensing, the bulk of the processing takes place in an 'inner loop' with a large number of simple operations. For these algorithms, dramatic speedups can often be obtained with specialized hardware. The difficulty and expense of digital design continues to limit applicability of this approach, but the development of new design tools is making this approach more feasible, and some notable successes have been reported. On the other hand, it is often the case that processing can also be accelerated by adopting a more sophisticated algorithm design. Unfortunately, a more sophisticated algorithm is much harder to implement in hardware, so these approaches are often at odds with each other. With careful planning, however, it is sometimes possible to combine software and hardware design in such a way that each complements the other, and the final implementation achieves speedup that would not have been possible with a hardware-only or a software-only solution. We will in particular discuss the co-design of software and hardware to achieve substantial speedup of algorithms for multispectral image segmentation and for endmember identification.

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8 p.

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  • Submitted to: SPIE Proceedings, July 29 to August 3, 2001, San Diego, CA

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  • Report No.: LA-UR-01-3597
  • Grant Number: none
  • Office of Scientific & Technical Information Report Number: 975609
  • Archival Resource Key: ark:/67531/metadc926714

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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Creation Date

  • January 1, 2001

Added to The UNT Digital Library

  • Nov. 13, 2016, 7:26 p.m.

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  • Dec. 9, 2016, 10:57 p.m.

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Theiler, J. P. (James P.); Frigo, J. (Janette); Gokhale, M. (Maya) & Szymanski, J. J. (John J.). Co-design of software and hardware to implement remote sensing algorithms, article, January 1, 2001; United States. (digital.library.unt.edu/ark:/67531/metadc926714/: accessed November 14, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.