Paper
3 September 1993 Image accuracy and representational enhancement through low-level multisensor integration techniques
James E. Baker
Author Affiliations +
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.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James E. Baker "Image accuracy and representational enhancement through low-level multisensor integration techniques", Proc. SPIE 1956, Sensor Fusion and Aerospace Applications, (3 September 1993); https://doi.org/10.1117/12.155083
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Sensors

Multispectral imaging

Image sensors

Image enhancement

Reflectivity

Image fusion

Sensor fusion

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