Optimizing codes for compressed ultrafast photography by the genetic algorithm
Abstract
The compressed ultrafast photography (CUP) technique, providing the fastest receive-only camera so far, has shown to be a well-established tool to capture the ultrafast dynamical scene. This technique is based on random codes to encode and decode the ultrafast dynamical scene by a compressed sensing algorithm. The choice of random codes significantly affects the image reconstruction quality. Therefore, it is important to optimize the encoding codes. Here, we develop a new scheme to obtain the optimized codes by combining a genetic algorithm (GA) into the CUP technique. First, we measure the dynamical scene by the CUP system with random codes and obtain the dynamical scene image at each moment. Second, we use these reconstructed dynamical scene images as the optimization target and optimize the encoding codes based on the GA. Finally, we utilize the optimized codes to recapture the dynamical scene and improve the image reconstruction quality. We validate our optimization scheme by the numerical simulation of a moving double-semielliptical spot and the experimental demonstration of a time- and space-evolving pulsed laser spot.
Additional Information
© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement. Received 30 October 2017; revised 16 December 2017; accepted 19 December 2017 (Doc. ID 309354); published 1 February 2018. Funding: National Natural Science Foundation of China (NSFC) (11474096, 11727810, 11774094, 61720106009); Science and Technology Commission of Shanghai Municipality (STCSM) (16520721200, 17ZR146900).Attached Files
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Additional details
- Eprint ID
- 85181
- Resolver ID
- CaltechAUTHORS:20180307-130604402
- National Natural Science Foundation of China
- 11474096
- National Natural Science Foundation of China
- 11727810
- National Natural Science Foundation of China
- 11774094
- National Natural Science Foundation of China
- 61720106009
- Science and Technology Commission of Shanghai Municipality
- 16520721200
- Science and Technology Commission of Shanghai Municipality
- 17ZR146900
- Created
-
2018-03-07Created from EPrint's datestamp field
- Updated
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2021-11-15Created from EPrint's last_modified field