Paper
26 January 2006 Virtual confocal microscopy
Author Affiliations +
Proceedings Volume 6056, Three-Dimensional Image Capture and Applications VII; 605607 (2006) https://doi.org/10.1117/12.650778
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
There is a need for persistent-surveillance assets to capture high-resolution, three-dimensional data for use in assisted target recognizing systems. Passive electro-optic imaging systems are presently limited by their ability to provide only 2-D measurements. We describe a methodology and system that uses existing technology to obtain 3-D information from disparate 2-D observations. This data can then be used to locate and classify objects under obscurations and noise. We propose a novel methodology for 3-D object reconstruction through use of established confocal microscopy techniques. A moving airborne sensing platform captures a sequence of geo-referenced, electro-optic images. Confocal processing of this data can synthesize a large virtual lens with an extremely sharp (small) depth of focus, thus yielding a highly discriminating 3-D data collection capability based on 2-D imagery. This allows existing assets to be used to obtain high-quality 3-D data (due to the fine z-resolution). This paper presents a stochastic algorithm for reconstruction of a 3-D target from a sequence of affine projections. We iteratively gather 2-D images over a known path, detect target edges, and aggregate the edges in 3-D space. In the final step, an expectation is computed resulting in an estimate of the target structure.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Philip M. Hanna, Brian D. Rigling, and Edmund G. Zelnio "Virtual confocal microscopy", Proc. SPIE 6056, Three-Dimensional Image Capture and Applications VII, 605607 (26 January 2006); https://doi.org/10.1117/12.650778
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Cited by 1 scholarly publication.
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KEYWORDS
3D acquisition

Confocal microscopy

3D image processing

Sensors

Edge detection

Clouds

Detection and tracking algorithms

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