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arXiv Computer Vision By Xining Ge, Ziteng Cui, Shuhong Liu

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

Read the original on arXiv Computer Vision →

ASTRA-SR is a blind single‑frame restoration framework designed for ground‑based planetary imaging, addressing atmospheric turbulence, sensor noise, and limited sampling. It is trained on a physics‑grounded synthetic dataset that uses high‑dynamic‑range spacecraft RAW observations as clean sources and synthesizes low‑resolution inputs with realistic turbulence, PSFs, and noise. The method first produces a noise‑suppressed but blur‑retaining low‑resolution image, then restores spatial structure via multiscale processing and refines high‑resolution detail with serial spatial‑amplitude refinement, achieving a 0.49 dB PSNR gain over the strongest baseline approaches.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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