Image quality recovery in binary ghost imaging by adding random noise
Abstract
When the sampling data of ghost imaging is recorded with less bits, i.e., experiencing quantization, decline of image quality is observed. The less bits used, the worse image one gets. Dithering, which adds suitable random noise to the raw data before quantization, is proved to be capable of compensating image quality decline effectively, even for the extreme binary sampling case. A brief explanation and parameter optimization of dithering are given.
- Publication:
-
Optics Letters
- Pub Date:
- April 2017
- DOI:
- 10.1364/OL.42.001640
- arXiv:
- arXiv:1702.08687
- Bibcode:
- 2017OptL...42.1640L
- Keywords:
-
- Physics - Optics
- E-Print:
- 8 pages, 7 figures