Computer Science – Performance
Scientific paper
Oct 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005spie.5964..236g&link_type=abstract
Advances in Optical Thin Films II. Edited by Amra, Claude; Kaiser, Norbert; Macleod, H. Angus. Proceedings of the SPIE, Volume
Computer Science
Performance
Scientific paper
Within the scope of this paper a both compact and economical data acquisition system for multispecral images is described. It consists of a CCD camera, a liquid crystal tunable filter in combination with an associated concept for data processing. Despite of their limited functionality (e.g.regarding calibration) in comparison with commercial systems such as AVIRIS the use of these upcoming compact multispectral camera systems can be advantageous in many applications. Additional benefit can be derived adding online data processing. In order to maintain the systems low weight and price this work proposes to separate data acquisition and processing modules, and transmit pre-processed camera data online to a stationary high performance computer for further processing. The inevitable data transmission has to be optimised because of bandwidth limitations. All mentioned considerations hold especially for applications involving mini-unmanned-aerial-vehicles (mini-UAVs). Due to their limited internal payload the use of a lightweight, compact camera system is of particular importance. This work emphasises on the optimal software interface in between pre-processed data (from the camera system), transmitted data (regarding small bandwidth) and post-processed data (based on high performance computer). Discussed parameters are pre-processing algorithms, channel bandwidth, and resulting accuracy in the classification of multispectral image data. The benchmarked pre-processing algorithms include diagnostic statistics, test of internal determination coefficients as well as loss-free and lossy data compression methods. The resulting classification precision is computed in comparison to a classification performed with the original image dataset.
Groh Christine
Rothe Hendrik
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