Abstract
Super-resolution (SR) image processing describes any technique by which the resolution of an imaging system is enhanced. Normally, the resolution being enhanced is spatial; images are processed to provide noise reduction, sub-pixel image localization, etc. Less often, it is used to enhance temporal properties - for example, to derive a higher framerate sequence from one or more lower framerate sequences. Time domain continuous imaging (TDCI) representations are inherently frameless, representing a time-varying scene as a compressed continuous waveform per pixel, but they still imply finite temporal resolution and accuracy. This paper explores computational methods by which the temporal resolution can be enhanced and temporal noise reduced using a TDCI representation.
| Original language | English |
|---|---|
| Pages (from-to) | 87-93 |
| Number of pages | 7 |
| Journal | IS and T International Symposium on Electronic Imaging Science and Technology |
| DOIs | |
| State | Published - 2017 |
| Event | Computational Imaging XV 2017 - Burlingame, United States Duration: Jan 29 2017 → Feb 2 2017 |
Bibliographical note
Funding Information:This work is supported in part under NSF Award #1422811, CSR: Small: Computational Support for Time Domain Continuous Imaging.
Funding
This work is supported in part under NSF Award #1422811, CSR: Small: Computational Support for Time Domain Continuous Imaging.
| Funders | Funder number |
|---|---|
| National Sleep Foundation | |
| Center for Strategic Research | |
| National Science Foundation (NSF) | 1422811 |
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
- Human-Computer Interaction
- Software
- Electrical and Electronic Engineering
- Atomic and Molecular Physics, and Optics
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