English(EN) The First Challenge on Remote Sensing Infrared Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

NTIRE 2026 挑战赛推动遥感红外图像超分辨率技术发展

作者 PulseAugur 编辑部 · [2 个来源] · 2026-04-23 06:07

研究人员开发了一个用于增强遥感红外图像分辨率的双分支系统，结合了HAT-L分支和MambaIRv2-L分支。该方法通过整合局部和全局建模，解决了热成像的独特挑战，如纹理较弱和对不稳定锐化的敏感性。该系统作为NTIRE 2026红外图像超分辨率挑战赛的解决方案提出，在关键指标上优于单个分支。 AI

影响推动红外图像超分辨率技术的发展，可能改进遥感应用中的分析。

排序理由这是一篇研究论文，详细介绍了一种针对特定AI任务的新颖方法及其在挑战赛中的表现。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

报道来源 [2]

arXiv cs.CV TIER_1 English(EN) · Xining Ge, Gengjia Chang, Weijun Yuan, Zhan Li, Zhanglu Chen, Boyang Yao, Yihang Chen, Yifan Deng, Shuhong Liu · 2026-04-28 04:00

Dual-Branch Remote Sensing Infrared Image Super-Resolution

arXiv:2604.10112v2 Announce Type: replace Abstract: Remote sensing infrared image super-resolution aims to recover sharper thermal observations from low-resolution inputs while preserving target contours, scene layout, and radiometric stability. Unlike visible-image super-resolut…
arXiv cs.CV TIER_1 English(EN) · Adrien Gressin · 2026-04-23 06:07

The First Challenge on Remote Sensing Infrared Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

This paper presents the NTIRE 2026 Remote Sensing Infrared Image Super-Resolution (x4) Challenge, one of the associated challenges of NTIRE 2026. The challenge aims to recover high-resolution (HR) infrared images from low-resolution (LR) inputs generated through bicubic downsampl…