English(EN) InfScene-SR: Seamless Super-Resolution of Arbitrarily Large Remote-Sensing Scenes via Variance-Preserving Joint Denoising

InfScene-SR 实现大尺寸遥感场景的无缝超分辨率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-01 04:00

研究人员开发了 InfScene-SR，一种使用扩散模型对大尺寸遥感场景进行无缝超分辨率的新方法。该方法解决了当前扩散模型通常局限于小尺寸、固定图像裁剪的局限性。InfScene-SR 采用一种称为空间解耦方差校正 (SDVC) 的方差校正融合技术，能够生成任意大尺寸的场景。该方法支持跨 GPU 并行处理，并在保持清晰度、保真度和接缝连续性方面表现出色，即使在植物分割等下游任务中也是如此。 AI

影响这项研究推进了扩散模型处理大规模图像的能力，有望改进遥感和地理空间分析等领域的应用。

排序理由发布了一篇详细介绍一种新图像超分辨率方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Shoukun Sun, Zhe Wang, Xiang Que, Jiyin Zhang, Xiaogang Ma · 2026-09-01 04:00

InfScene-SR：通过保持方差的联合去噪实现任意大遥感场景的无缝超分辨率

arXiv:2602.19736v3 Announce Type: replace Abstract: Diffusion models now give the best perceptual quality in super-resolution (SR), but their architecture and training confine them to small fixed crops. Operational remote sensing needs seamless scenes orders of magnitude larger. …

本文如何被排名

报道来源 [1]

InfScene-SR：通过保持方差的联合去噪实现任意大遥感场景的无缝超分辨率

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