dc.contributor.author |
Stoltz, George G
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|
dc.contributor.author |
Stoltz, M
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|
dc.date.accessioned |
2021-02-09T09:57:36Z |
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dc.date.available |
2021-02-09T09:57:36Z |
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dc.date.issued |
2020-09 |
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dc.identifier.citation |
Stoltz, G.G. & Stoltz, M. 2020. Performance estimation of a real-time Rosette imager. http://hdl.handle.net/10204/11735 . |
en_ZA |
dc.identifier.uri |
http://hdl.handle.net/10204/11735
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dc.description.abstract |
In this paper, we model a real-time feasible rosette imager, consisting of a rosette scanner, an optical sensor and a deterministic image reconstruction algorithm. We fine-tune the rosette imager through selecting the appropriate sensor field of view and rosette pattern. The sensor field of view is determined through a greedy approach using uniform random sampling. Furthermore, the optimal rosette pattern is selected by determining which pattern best covers the imaging area uniformly. We explore image sparsity, image decimation and Gaussian filtering in a well-known natural data set and dead leaves data set using the PSNR, Peak-Signal-to-Noise Ratio. This exploration helps to establish a connection between PSNR and image sparsity. Furthermore, we compare various rosette imager configurations in a Bayesian framework. We also conclude that the rosette imager does not outperform a focal-plane array of equivalent samples in terms of image quality but can match the performance. |
en_US |
dc.format |
Full text |
en_US |
dc.language.iso |
en |
en_US |
dc.relation.uri |
doi.org/10.1117/12.2575060 |
en_US |
dc.relation.uri |
https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11537.toc |
en_US |
dc.relation.uri |
https://doi.org/10.1117/12.2575060 |
en_US |
dc.relation.uri |
9781510638884 |
en_US |
dc.relation.uri |
0277-786X |
en_US |
dc.relation.uri |
1996-756X |
en_US |
dc.source |
Proceedings of SPIE, Volume 11537, Electro-Optical and Infrared Systems: Technology and Applications XVII, 21-25 September 2020 |
en_US |
dc.subject |
Image formation |
en_US |
dc.subject |
Compressed sensing |
en_US |
dc.subject |
Rosette scanning systems |
en_US |
dc.title |
Performance estimation of a real-time Rosette imager |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.description.pages |
16pp |
en_US |
dc.description.note |
Copyright: SPIE 2020. Due to copyright restrictions, the attached PDF file contains the accepted version of the published item. |
en_US |
dc.description.cluster |
Defence and Security |
|
dc.description.impactarea |
Optronic Sensor Systems |
en_US |
dc.identifier.apacitation |
Stoltz, G. G., & Stoltz, M. (2020). Performance estimation of a real-time Rosette imager. http://hdl.handle.net/10204/11735 |
en_ZA |
dc.identifier.chicagocitation |
Stoltz, George G, and M Stoltz. "Performance estimation of a real-time Rosette imager." <i>Proceedings of SPIE, Volume 11537, Electro-Optical and Infrared Systems: Technology and Applications XVII, 21-25 September 2020</i> (2020): http://hdl.handle.net/10204/11735 |
en_ZA |
dc.identifier.vancouvercitation |
Stoltz GG, Stoltz M, Performance estimation of a real-time Rosette imager; 2020. http://hdl.handle.net/10204/11735 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Stoltz, George G
AU - Stoltz, M
AB - In this paper, we model a real-time feasible rosette imager, consisting of a rosette scanner, an optical sensor and a deterministic image reconstruction algorithm. We fine-tune the rosette imager through selecting the appropriate sensor field of view and rosette pattern. The sensor field of view is determined through a greedy approach using uniform random sampling. Furthermore, the optimal rosette pattern is selected by determining which pattern best covers the imaging area uniformly. We explore image sparsity, image decimation and Gaussian filtering in a well-known natural data set and dead leaves data set using the PSNR, Peak-Signal-to-Noise Ratio. This exploration helps to establish a connection between PSNR and image sparsity. Furthermore, we compare various rosette imager configurations in a Bayesian framework. We also conclude that the rosette imager does not outperform a focal-plane array of equivalent samples in terms of image quality but can match the performance.
DA - 2020-09
DB - ResearchSpace
DP - CSIR
J1 - Proceedings of SPIE, Volume 11537, Electro-Optical and Infrared Systems: Technology and Applications XVII, 21-25 September 2020
KW - Image formation
KW - Compressed sensing
KW - Rosette scanning systems
LK - https://researchspace.csir.co.za
PY - 2020
T1 - Performance estimation of a real-time Rosette imager
TI - Performance estimation of a real-time Rosette imager
UR - http://hdl.handle.net/10204/11735
ER - |
en_ZA |
dc.identifier.worklist |
24002 |
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