SOURCE-LINKED INTELLIGENCE

ASTRA-SR: Atmospheric Seeing and Turbulence Restoration for Astronomical Image Super-Resolution

arXiv · AI, language, vision and robotics · article · Sep 22, 2026 · UTC

Ground-based planetary imaging suffers from atmospheric turbulence, sensor noise, and limited sampling, making restoration a joint denoising, deblurring, and super-resolution problem. We present ASTRA-SR, a blind single-frame restoration framework trained on a physics-grounded synthetic dataset. High-dynamic-range spacecraft RAW observations serve as clean sources, and paired LR inputs are synthesized using measured layer-integrated turbulence strengths, propagated moving phase screens, exposure-averaged spatially varying PSFs, and sensor noise.ASTRA-SR first estimates a noise-suppressed but b

Read original source ↗ Open in workspace

recordType

paper

region

Global