AI RESEARCH
HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation
arXiv CS.CV
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ArXi:2605.13581v1 Announce Type: new Hyperspectral image (HSI) restoration is crucial for reliable analysis, as real HSIs suffer from degradations like noise, blur, and resolution loss. However, existing models trained on source data often fail on target domains lacking clean references, a common occurrence in practice. To address this issue, we present HIR-ALIGN, a plug-and-play target-adaptive augmentation framework that enhances hyperspectral image restoration by augmenting limited