@InProceedings{fallah-adl:data,
  author = {Hassan Fallah-Adl and Joseph J\'aJ\'a and Shunlin Liang and Yoram
  J. Kaufman and John Townshend},
  title = {Efficient Algorithms for Atmospheric Correction of Remotely Sensed
  Data},
  booktitle = {Proceedings of Supercomputing '95},
  year = {1995},
  publisher = {IEEE Computer Society Press},
  address = {San Diego, CA},
  URL = {http://www.supercomp.org/sc95/proceedings/511_HFAD/SC95.HTM},
  keywords = {remote sensing, parallel I/O application, pario-bib},
  abstract = {Remotely sensed imagery has been used for developing and
  validating various studies regarding land cover dynamics. However, the large
  amounts of imagery collected by the satellites are largely contaminated by
  the effects of atmospheric particles. The objective of atmospheric correction
  is to retrieve the surface reflectance from remotely sensed imagery by
  removing the atmospheric effects. We introduce a number of computational
  techniques that lead to a substantial speedup of an atmospheric correction
  algorithm based on using look-up tables. Excluding I/O time, the previous
  known implementation processes one pixel at a time and requires about 2.63
  seconds per pixel on a SPARC-10 machine, while our implementation is based on
  processing the whole image and takes about 4-20 microseconds per pixel on the
  same machine. We also develop a parallel version of our algorithm that is
  scalable in terms of both computation and I/O. Experimental results obtained
  show that a Thematic Mapper (TM) image (36 MB per band, 5 bands need to be
  corrected) can be handled in less than 4.3 minutes on a 32-node CM-5 machine,
  including I/O time.},
  comment = {Note proceedings only on CD-ROM or WWW.}
}