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Issue No.06 - Nov.-Dec. (2011 vol.13)
pp: 76-78
ABSTRACT
<p>Studying small particles is of interest to NASA scientists for many applications, such as characterizing the lunar and Martian dust environments. In this homework, we characterize the motion of small particles using image analysis.</p>
INDEX TERMS
Planetary lander, velocimetry, filtering, deconvolution, deblurring, scientific computing
CITATION
Nargess Memarsadeghi, Brent J. Bos, "NASA Computational Case Study Characterizing Moving Particles", Computing in Science & Engineering, vol.13, no. 6, pp. 76-78, Nov.-Dec. 2011, doi:10.1109/MCSE.2011.93
REFERENCES
1. B.J. Bos, S. Antonille, and N. Memarsadeghi, "Characterization of Moving Dust Particles," Proc. SPIE 7873, SPIE, 2011; doi:10.1117/12.872018.
2. B.J. Bos and W.M. Farrell, "Dust Flux Instrumentation for Mars Landers," Proc. 7th Int'l Conf. on Mars, Lunar and Planetary Institute, no. 1353, 2007, p. 3349.
3. R. Bracewell, The Fourier Transform and Its Applications, 3rd ed., McGraw-Hill, 1999.
4. D.S.C. Biggs, "Acceleration of Iterative Image-Restoration Algorithms," Applied Optics, vol. 36, no. 8, 1997, pp. 1766–1775.
5. R.J. Hanisch, R.L. White, and R.L. Gilliland, "Deconvolution of Hubble Space Telescope Images and Spectra," in Deconvolution of Images and Spectra, 2nd ed., Academic Press, 1997, pp. 310–356.
6. R.L. Easton Jr., Fourier Methods in Imaging, John Wiley & Sons, 2010.
7. J.R. Schott, Remote Sensing: The Image Chain Approach, 2nd ed., Oxford Univ. Press, 2007.
8. P.C. Hansen, J.G. Nagy, and D.P. O'Leary, Deblurring Images: Matrices, Spectra, and Filtering. Fundamentals of Algorithms, vol. 3, SIAM, 2006.
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