Multiview Imaging with Real-Time Microwave Camera from Known Positions
Abstract
This contribution shows the application of multiview processing technique to a recently-developed real-time 3D microwave camera. The camera, which operates based on efficient synthetic aperture radar (SAR) imaging techniques, provides a good trade-off between fast image production and image quality. These cameras, as it happens with standard optical cameras, provide a good image of a volume in front of their apertures, but they cannot provide information about the complete object under test. Furthermore, it is usually convenient to consider multiple view angles as the best quality image is achieved when the area to be image is parallel to the aperture (as the specular reflection is captured). In this paper, we illustrate how recently-developed techniques, inspired from computer vision approaches, can be used to merge multiple views to obtain a more complete image of an object.
Recommended Citation
J. Laviada et al., "Multiview Imaging with Real-Time Microwave Camera from Known Positions," Proceedings of the 2018 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting (2018, Boston, MA), Institute of Electrical and Electronics Engineers (IEEE), Jul 2018.
The definitive version is available at https://doi.org/10.1109/APUSNCURSINRSM.2018.8608615
Meeting Name
2018 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting (2018: Jul. 8-13, Boston, MA)
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Cameras; Microwave imaging; Microwave theory and techniques; Apertures; Real-time systems; Synthetic aperture radar
International Standard Book Number (ISBN)
978-1-5386-7102-3
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jul 2018
Comments
This work has been partially supported by the Ministerio de Ciencia e Innovación of Spain /FEDER under project TEC2014-55290-JIN.