arXiv:2601.23276v4 Announce Type: replace-cross
Abstract: Astronomical imaging remains noise-limited under practical observing conditions. Standard calibration pipelines remove structured artifacts b...
By Shuhong Liu, Xining Ge, Ziying Gu, Quanfeng Xu, Lin Gu, Ziteng Cui, Xuangeng Chu, Jun Liu, Dong Li, Tatsuya Harada
arXiv:2512. 11982v2 Announce Type: replace-cross Abstract: Finding scientifically interesting phenomena through slow manual labeling campaigns severely limits our ability to explore the billions of galaxy images produced by telescopes.
By Nolan Koblischke, Liam Parker, Francois Lanusse, Jo Bovy, Irina Espejo, Shirley Ho
The paper introduces a deep‑learning pipeline that improves detection of faint moving objects in optical space situational awareness imagery. It combines a Tiny‑U‑Net segmentation network to mask stars with a partial‑convolution variational autoencoder (astro‑VAE) that learns background statistics and performs context‑aware inpainting. The reconstructed, star‑free backgrounds are used as a preprocessing step before detection, and when integrated with a shift‑and‑stack scheme, the method shows high‑fidelity background reconstruction and significant enhancement of moving‑target detectability in real ground‑based telescope data.
By Angela Cratere, Luca Ghilardi, Vishnu Reddy, Francesco Dell'Olio, Charalampos S. Kouzinopoulos, Roberto Furfaro
arXiv:2606. 10197v1 Announce Type: cross Abstract: Integral field unit (IFU) spectroscopy provides spatially resolved spectra across galaxies, offering crucial insights into their evolution.
By Zehao Peng, Biprateep Dey, Chris J. Maddison, Joshua S. Speagle
Genesis is a generative engine that produces fully consistent multi‑scale satellite image pyramids by combining a vertical super‑resolution model with a horizontal mask‑based outpainting model. It addresses the lack of existing methods that can synthesize a complete quadtree from sparse seed tiles at arbitrary zoom levels and positions, ensuring coherence across both scale and space. The authors also release dense500, a comprehensive multi‑scale dataset and evaluation suite, to benchmark this new task.
By Subash Khanal, Yangzhi Cui, Daniel Cher, Eric Xing, Brian Wei, Srikumar Sastry, Nathan Jacobs
Gaussian Splatting has been recently explored for satellite 3D reconstruction, demonstrating flexibility and efficiency in representing radiometrically diverse satellite scenes. However, the limited top viewpoint of satellite imagery results in insufficient supervision on building facades, leaving surface holes and degraded visual fidelity.