Abstract
This paper summarizes our progress towards a first fully transparent, flexible, scalable, and disposable thin-film image sensor. In contrast to conventional image sensors, it does not capture pixels in image space on the sensor surface, but makes integral measurements in Radon space along the sensor׳s edges. Image reconstruction is achieved by inverse Radon transform. By stacking multiple layers, it enables a variety of information, such as color, dynamic range, spatial resolution, and defocus, to be sampled simultaneously. Lensless multi-focal imaging allows reconstructing an entire focal stack after only one recording. The focal stack can then be applied to estimate depth from defocus. Measuring and classifying directly in Radon space yields robust and high classification rates. Dimensionality reduction results in task-optimized classification sensors that record a minimal number of samples. This enables simple devices with low power consumption and fast read-out times.
| Original language | English |
|---|---|
| Pages (from-to) | 37-43 |
| Number of pages | 7 |
| Journal | Computers and Graphics |
| Volume | 53 |
| DOIs | |
| Publication status | Published - Dec 2015 |
Fields of science
- 102 Computer Sciences
- 102003 Image processing
- 102008 Computer graphics
- 102015 Information systems
- 102020 Medical informatics
- 103021 Optics
JKU Focus areas
- Engineering and Natural Sciences (in general)