2021/11/24 by T.I Liaudat, Jean‐Luc Starck, Liaudat, Tobias +5 · 2 citations
Biochemistry, Genetics and Molecular Biology · Engineering · Physics and Astronomy · #Adaptive optics and wavefront sensing #Advanced Fluorescence Microscopy Techniques #Advanced optical system design #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Optics (physics.optics)
paper · pdf · doi:10.48550/arxiv.2111.12541
openalex publication_date 2021/11/24 · openalex created_date 2022/11/22 · openalex updated_date 2026/07/28
We propose a paradigm shift in the data-driven modeling of the instrumental response field of telescopes. By adding a differentiable optical forward model into the modeling framework, we change the data-driven modeling space from the pixels to the wavefront. This allows to transfer a great deal of complexity from the instrumental response into the forward model while being able to adapt to the observations, remaining data-driven. Our framework allows a way forward to building powerful models that are physically motivated, interpretable, and that do not require special calibration data. We show that for a simplified setting of a space telescope, this framework represents a real performance breakthrough compared to existing data-driven approaches with reconstruction errors decreasing 5 fold at observation resolution and more than 10 fold for a 3x super-resolution. We successfully model chromatic variations of the instrument's response only using noisy broad-band in-focus observations.