Name
Abstract | ||
|---|---|---|
A large depth-of-field Particle Image Velocimeter (PIV) has been developed at NASA GSFC to characterize dynamic dust environments on planetary surfaces. This instrument detects and senses lofted dust particles. To characterize a dynamic planetary dust environment, the instrument would have to operate for at least several minutes during an observation period, easily producing more than a terabyte of data per observation. Given current technology, this amount of data would be very difficult to store onboard a spacecraft and downlink to Earth. We have been developing an autonomous image analysis algorithm architecture for the PIV instrument to greatly reduce the amount of data that it has to store and downlink. The algorithm analyzes PIV images and reduces the image information down to only the particle measurement data we are interested in receiving on the ground - typically reducing the amount of data to be handled by more than two orders of magnitude. We give a general description of the PIV algorithms and describe in detail the algorithm for estimating the direction and velocity of the traveling particles, which was done by taking advantage of the optical properties of moving dust particles along with image processing techniques. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1117/12.872018 | COMPUTATIONAL IMAGING IX |
Keywords | Field | DocType |
Planetary lander, velocimetry, compression, filtering, deconvolution, deblurring | Particle image velocimetry,Deblurring,Terabyte,Computer science,Remote sensing,Deconvolution,Image processing,Velocimetry,Particle,Spacecraft | Conference |
Volume | ISSN | Citations |
7873 | 0277-786X | 1 |
PageRank | References | Authors |
0.48 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brent J. Bos | 1 | 1 | 0.82 |
| Scott R. Antonille | 2 | 1 | 0.48 |
| Nargess Memarsadeghi | 3 | 33 | 7.70 |