@conference {14956,
	title = {Efficient algorithms for estimating atmospheric parameters for surface reflectance retrieval},
	booktitle = {Parallel Processing, 1996., Proceedings of the 1996 International Conference on},
	volume = {2},
	year = {1996},
	month = {1996/08//},
	pages = {132 -141 vol.2 - 132 -141 vol.2},
	abstract = {The objective of atmospheric correction is to retrieve the surface reflectance from remotely sensed imagery by removing the atmospheric effects. We introduce an efficient algorithm to estimate the optical characteristics of the TM imagery and to remove the atmospheric effects from it. Our algorithm introduces a set of techniques to significantly improve the quality of the retrieved images. We pay a particular attention to the computational efficiency of the algorithm thereby allowing us to correct large TM images quite fast. We also provide a parallel implementation of our algorithm and show its portability and scalability on several parallel machines},
	keywords = {Atmospheric, correction;atmospheric, effects;atmospheric, imagery;scalability;surface, parameters;portability;remotely, reconstruction;photoreflectance;remote, reflectance, reflectance;surface, retrieval;image, sensed, sensing;},
	doi = {10.1109/ICPP.1996.537392},
	author = {Fallah-Adl,H. and JaJa, Joseph F. and Liang,Shunlin}
}
@article {14967,
	title = {Fast algorithms for removing atmospheric effects from satellite images},
	journal = {Computational Science Engineering, IEEE},
	volume = {3},
	year = {1996},
	month = {1996///summer},
	pages = {66 - 77},
	abstract = {The varied features of the earth{\textquoteright}s surface each reflect sunlight and other wavelengths of solar radiation in a highly specific way. This principle provides the foundation for the science of satellite based remote sensing. A vexing problem confronting remote sensing researchers, however, is that the reflected radiation observed from remote locations is significantly contaminated by atmospheric particles. These aerosols and molecules scatter and absorb the solar photons reflected by the surface in such a way that only part of the surface radiation can be detected by a sensor. The article discusses the removal of atmospheric effects due to scattering and absorption, ie., atmospheric correction. Atmospheric correction algorithms basically consist of two major steps. First, the optical characteristics of the atmosphere are estimated. Various quantities related to the atmospheric correction can then be computed by radiative transfer algorithms, given the atmospheric optical properties. Second, the remotely sensed imagery is corrected by inversion procedures that derive the surface reflectance. We focus on the second step, describing our work on improving the computational efficiency of the existing atmospheric correction algorithms. We discuss a known atmospheric correction algorithm and then introduce a substantially more efficient version which we have devised. We have also developed a parallel implementation of our algorithm},
	keywords = {algorithms;reflectivity;remote, Atmospheric, based, computing;image, correction;atmospheric, effects;atmospheric, efficiency;inversion, enhancement;parallel, imagery;satellite, images;solar, implementation;reflected, particles;computational, photons;surface, procedures;parallel, radiation;atmospheric, radiation;remote, reflectance;atmospheric, remote, research;remotely, sensed, sensing, sensing;, sensing;satellite, techniques;geophysics},
	isbn = {1070-9924},
	doi = {10.1109/99.503316},
	author = {Fallah-Adl,H. and JaJa, Joseph F. and Liang, S. and Townshend,J. and Kaufman,Y.J.}
}
@conference {14955,
	title = {Efficient Algorithms for Atmospheric Correction of Remotely Sensed Data},
	booktitle = {Supercomputing, 1995. Proceedings of the IEEE/ACM SC95 Conference},
	year = {1995},
	month = {1995///},
	pages = {12 - 12},
	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.},
	keywords = {Atmospheric, AVHRR;, computing;, correction;, high, I/O;, Parallel, performance, processing;, remote, scalable, sensing;, TM;},
	doi = {10.1109/SUPERC.1995.242453},
	author = {Fallah-Adl,H. and JaJa, Joseph F. and Liang,Shunlin and Kaufman,Y.J. and Townshend,J.}
}
