English(EN) AstraMoE-SR: Trajectory-Guided Diffusion for Blind Satellite Jitter Deblurring and Super-Resolution

新AI框架解决卫星图像去模糊和超分辨率问题

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-10 04:00

研究人员开发了AstraMoE-SR，一个新颖的单图像框架，旨在同时对卫星图像进行去模糊和提高分辨率。该方法解决了推扫式卫星成像中平台抖动带来的挑战，平台抖动会导致空间变化的运动模糊。与现有方法不同，AstraMoE-SR不需要辅助测量或显式的模糊核估计。相反，它通过将退化建模为局部曝光轨迹来推断相机的运动，并利用条件扩散模型来预测这些轨迹，然后指导潜在扩散骨干进行对齐和重建。该框架在DOTA-v1.0数据集上表现出卓越的性能，在多个保真度指标上优于先前的方法和无恢复基线。 AI

影响这项研究通过在无需辅助数据的情况下实现更准确的去模糊和超分辨率，有望提高各种应用中卫星图像的质量。

排序理由该项目是一篇研究论文，详细介绍了一种用于图像处理的新AI模型。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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arXiv cs.LG TIER_1 English(EN) · Yi-Chung Lai, Chin-Tien Wu, Yu-Chih Chen · 2026-09-10 04:00

AstraMoE-SR：轨迹引导扩散用于盲卫星抖动去模糊和超分辨率

arXiv:2609.07012v1 Announce Type: cross Abstract: Pushbroom satellite imaging couples limited spatial resolution with platform attitude instability. Platform jitter produces spatially varying motion blur because each scan line is acquired under a different instantaneous attitude,…

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AstraMoE-SR：轨迹引导扩散用于盲卫星抖动去模糊和超分辨率

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