Amplifying the imaging power of digital sky surveys with space telescopes data and generative AI

2026-08-20

AI Summary

研究利用生成式AI提升地面望远镜拍摄的星系图像质量至空间望远镜水平，结合了地面观测的大通量与空间望远镜的高清晰度。

Abstract

While Digital sky surveys provide excellent throughput of image data and can cover a large footprint, their imaging power is normally inferior to that of space-based telescopes. Space-based telescopes, on the other hand, provide excellent imaging power and can image the deep Universe, but cannot provide the same throughput as advanced ground-based sky surveys. Here, we utilize generative AI to elevate the quality of galaxy images taken by ground-based telescopes to the level of details enabled by space telescopes. The solution is based on the nature of galaxy shapes, allowing generative AI trained on space-based images to convert weak signal into detailed and clear galaxy images. The method allows for combining the high throughput of ground-based sky surveys with the image quality of space-based telescopes. The source code for the method is available, as well as paired training data and a catalog of 63,202 galaxy images enhanced by the proposed method. We also provide a software tool that encapsulates the entire pipeline and the custom generative AI model to generate galaxy images with enhanced quality.

Problem

• Digital sky surveys
• space telescopes
• imaging power
• throughput
• galaxy images

Innovation

• generative AI
• galaxy images
• image enhancement
• space telescopes
• ground-based surveys