# Deeper detection limits in astronomical imaging using self-supervised spatiotemporal denoising

arXiv: https://arxiv.org/abs/2602.17205 · HTML: https://mlsanity.com/paper/2602.17205/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 71 references that are in the map.
- First posted on arXiv 19 Feb 2026.

## Builds on (most cited first, 1 of 1)

- [Weak-signal extraction enabled by deep-neural-network denoising of diffraction data](https://mlsanity.com/paper/2209.09247/) (2022)

## Built on by (most cited first, 6 of 6)

- [RAWild: Sensor-Agnostic RAW Object Detection via Physics-Guided Curve and Grid Modeling](https://mlsanity.com/paper/2605.05941/) (2026)
- [SCOUT: Fast Spectral CT Imaging in Ultra LOw-data Regimes via PseUdo-label GeneraTion](https://mlsanity.com/paper/2603.00687/) (2026)
- [AstroSURE: Learning to Remove Noise from Astronomical Images Without Ground Truth Data](https://mlsanity.com/paper/2604.16793/) (2026)
- [Pre-training Enables Extraordinary All-optical Image Denoising](https://mlsanity.com/paper/2605.07810/) (2026)
- [Poisson2Gaussian: Noise Gaussianization to Enhance Image Denoising](https://mlsanity.com/paper/2606.23098/) (2026)
- [ASTRA-SR: Atmospheric Seeing and Turbulence Restoration for Astronomical Image Super-Resolution](https://mlsanity.com/paper/2609.26731/) (2026)

## Abstract (arXiv)

The detection limit of astronomical imaging observations is limited by several noise sources. Some of that noise is correlated between neighbouring image pixels and exposures, so in principle could be learned and corrected. We present an astronomical self-supervised transformer-based denoising algorithm (ASTERIS), that integrates spatiotemporal information across multiple exposures. Benchmarking on mock data indicates that ASTERIS improves detection limits by 1.0 magnitude at 90% completeness and purity, while preserving the point spread function and photometric accuracy. Observational validation using data from the James Webb Space Telescope (JWST) and Subaru telescope identifies previously undetectable features, including low-surface-brightness galaxy structures and gravitationally-lensed arcs. Applied to deep JWST images, ASTERIS identifies three times more redshift > 9 galaxy candidates, with rest-frame ultraviolet luminosity 1.0 magnitude fainter, than previous methods.