Publication in Optics Letters highlighted as Editor's Pick
Maximum-likelihood estimation in ptychography in the presence of Poisson–Gaussian noise statistics
We are excited to share our latest research published in Optics Letters, which has been highlighted as an Editor's pick.
Have you ever noticed how photos can look grainy, especially in low light? That's due to measurement noise, which is also a challenge in computational imaging. In our paper, we tackle this issue head-on. We utilize a method known as Maximum-likelihood estimation for use in ptychography—a computational imaging method to reconstruct images from diffraction patterns.
The crux of our work is dealing with the "mixed noise" that arises from the quantum nature of light and the inevitable noise from camera sensors. By characterizing the readout noise statistics of a camera sensor beforehand, one can significantly enhance image clarity in computational imaging in low-light scenarios.
This work has practical uses beyond scientific research, such as improving medical diagnostics and materials analysis. It's a step towards clearer images, even in less-than-ideal lighting conditions.
Maximum-likelihood estimation in ptychography in the presence of Poisson–Gaussian noise statistics
Jacob Seifert (NP), Yifeng Shao (NP), Rens van Dam (NP), Dorian Bouchet, Tristan van Leeuwen, and Allard P. Mosk (NP), Opt. Lett. 48, 6027-6030 (2023)
Publication date: 14th November 2023
https://doi.org/10.1364/OL.502344