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Proceedings Paper

Image accuracy and representational enhancement through low-level multisensor integration techniques
Author(s): James E. Baker
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Paper Abstract

This research focuses on data and conceptual enhancement algorithms. To be useful in many real-world applications, e.g., autonomous or teleoperated robotics, real-time feedback is critical. Unfortunately, many multi-sensor integration (MSI)/image processing algorithms require significant processing time. The basic direction of this research is the potentially faster and more robust formation of `clusters from pixels' rather than the slower process of extracting `clusters from images.' Techniques are evaluated on actual multi-modal sensor data obtained from a laser range camera, i.e., range and reflectance images. A suite of over thirty conceptual enhancement techniques are developed, evaluated, and compared on this sensor domain. The overall result is a general-purpose, MSI conceptual enhancement approach which can be efficiently implemented and used to supply input to a variety of high-level processes, including: object recognition, path planning, and object avoidance systems.

Paper Details

Date Published: 3 September 1993
PDF: 17 pages
Proc. SPIE 1956, Sensor Fusion and Aerospace Applications, (3 September 1993); doi: 10.1117/12.155083
Show Author Affiliations
James E. Baker, Oak Ridge National Lab. (United States)


Published in SPIE Proceedings Vol. 1956:
Sensor Fusion and Aerospace Applications
Jake K. Aggarwal; Nagaraj Nandhakumar, Editor(s)

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