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Proceedings Paper

Imaging and localization in turbid media
Author(s): Charles L. Matson; Hanli Liu; Barbara Tehan Landesman; Ryan Christopher
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Paper Abstract

We apply out previously-developed turbid-media backpropagation algorithm to imaging extended objects imbedded in turbid media such as clouds. Although the backpropagation algorithm was developed initially for biomedical applications, the underlying development is general enough to encompass imaging objects imbedded in any sort of turbid media whose scattering properties dominate their absorption properties. For non-biomedical applications, imaging data is usually obtained only for a limited number of view angles. As a result, we look at the potential of the backpropagation algorithm to reconstruct an image of an object, imbedded in a cloud, from a single view. Using both computer-simulated data and laboratory data, we show that the backpropagation algorithm successfully increases resolution in these types of images. Because the backpropagation algorithm incorporates a depth-dependent deconvolution filter, it turns out that the optimal image quality obtained in the reconstruction occurs for the deconvolution filter which corresponds to the location of the object in the medium. This surprising result permits object localization in the range dimension even when the illuminating radiation is continuous-wave illumination, such as sunlight.

Paper Details

Date Published: 10 December 1999
PDF: 8 pages
Proc. SPIE 3866, Optics in Atmospheric Propagation and Adaptive Systems III, (10 December 1999); doi: 10.1117/12.371336
Show Author Affiliations
Charles L. Matson, Air Force Research Lab. (United States)
Hanli Liu, Univ. of Texas/Arlington (United States)
Barbara Tehan Landesman, Applied Technology Associates (United States)
Ryan Christopher, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 3866:
Optics in Atmospheric Propagation and Adaptive Systems III
Anton Kohnle; John D. Gonglewski, Editor(s)

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