DSR-Net: Dynamic Star Map Denoising Algorithm Based on Deep Reinforcement Learning

As astronomical observation technology continues to progress, obtaining high-quality star maps provides us with valuable opportunities to explore the universe. However, The acquired star maps are often affected by various random noises, including speckle noise, Poisson noise, Impulse noise, Thermal

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.4108/eai.21-11-2024.2354638
Primary Topic
Astronomical Observations and Instrumentation
Type
article
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article

DSR-Net: Dynamic Star Map Denoising Algorithm Based on Deep Reinforcement Learning

Yifan Zhao, Shaochen Jiang, Shiji Song
Astronomical Observations and Instrumentation
article

DSR-Net: Dynamic Star Map Denoising Algorithm Based on Deep Reinforcement Learning

Yifan Zhao, Shaochen Jiang, Shiji Song
article en

Abstract

As astronomical observation technology continues to progress, obtaining high-quality star maps provides us with valuable opportunities to explore the universe. However, The acquired star maps are often affected by various random noises, including speckle noise, Poisson noise, Impulse noise, Thermal

Openalex Percentile: Top 94%
Astronomical Observations and Instrumentation
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DSR-Net: Dynamic Star Map Denoising Algorithm Based on Deep Reinforcement Learning — Yifan Zhao, Shaochen Jiang, et al. · (2025) | TGRS Research Map | TGRS