Papers Hyperspectral Image Super-Resolution
“Hyperspectral Image Super-Resolution” 태그가 달린 논문 52편 · 필터 해제
SpectraLift: Physics-Guided Spectral-Inversion Network for Self-Supervised Hyperspectral Image Super-Resolution
High-spatial-resolution hyperspectral images (HSI) are essential for applications such as remote sensing and medical imaging, yet HSI sensors inherently trade spatial detail for spectral richness. Fusing high-spatial-res…
Hyperspectral Image Super-ResolutionImage Super-ResolutionSpectral ReconstructionSSIM+1Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution
Even without auxiliary images, single hyperspectral image super-resolution (SHSR) methods can be designed to improve the spatial resolution of hyperspectral images. However, failing to explore coherence thoroughly along …
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionDACN: Dual-Attention Convolutional Network for Hyperspectral Image Super-Resolution
2D convolutional neural networks (CNNs) have attracted significant attention for hyperspectral image super-resolution tasks. However, a key limitation is their reliance on local neighborhoods, which leads to a lack of gl…
Hyperspectral Image Super-ResolutionImage Super-ResolutionL2 RegularizationSuper-ResolutionHSRMamba: Efficient Wavelet Stripe State Space Model for Hyperspectral Image Super-Resolution
Single hyperspectral image super-resolution (SHSR) aims to restore high-resolution images from low-resolution hyperspectral images. Recently, the Visual Mamba model has achieved an impressive balance between performance …
Computational EfficiencyHyperspectral Image Super-ResolutionImage GenerationImage Super-Resolution+2A Fusion-Guided Inception Network for Hyperspectral Image Super-Resolution
The fusion of low-spatial-resolution hyperspectral images (HSIs) with high-spatial-resolution conventional images (e.g., panchromatic or RGB) has played a significant role in recent advancements in HSI super-resolution. …
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionUnaligned RGB Guided Hyperspectral Image Super-Resolution with Spatial-Spectral Concordance
Hyperspectral images super-resolution aims to improve the spatial resolution, yet its performance is often limited at high-resolution ratios. The recent adoption of high-resolution reference images for super-resolution i…
Hyperspectral Image Super-ResolutionImage Super-ResolutionOptical Flow EstimationSuper-ResolutionTowards Lightweight Hyperspectral Image Super-Resolution with Depthwise Separable Dilated Convolutional Network
Deep neural networks have demonstrated highly competitive performance in super-resolution (SR) for natural images by learning mappings from low-resolution (LR) to high-resolution (HR) images. However, hyperspectral super…
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionHSRMamba: Contextual Spatial-Spectral State Space Model for Single Image Hyperspectral Super-Resolution
Mamba has demonstrated exceptional performance in visual tasks due to its powerful global modeling capabilities and linear computational complexity, offering considerable potential in hyperspectral image super-resolution…
Hyperspectral Image Super-ResolutionImage Super-ResolutionMambaSuper-ResolutionRethinking the Upsampling Layer in Hyperspectral Image Super Resolution
Deep learning has achieved significant success in single hyperspectral image super-resolution (SHSR); however, the high spectral dimensionality leads to a heavy computational burden, thus making it difficult to deploy in…
Hyperspectral Image Super-ResolutionImage Super-ResolutionKnowledge DistillationSuper-ResolutionVolFormer: Explore More Comprehensive Cube Interaction for Hyperspectral Image Restoration and Beyond
Capitalizing on the talent of self-attention in capturing non-local features, Transformer architectures have exhibited remarkable performance in single hyperspectral image restoration. For hyperspectral images, each …
Hyperspectral Image Super-ResolutionImage RestorationImage Super-ResolutionSuper-ResolutionA Generalized Tensor Formulation for Hyperspectral Image Super-Resolution Under General Spatial Blurring
Hyperspectral super-resolution is commonly accomplished by the fusing of a hyperspectral imaging of low spatial resolution with a multispectral image of high spatial resolution, and many tensor-based approaches to this t…
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionTest-time Training for Hyperspectral Image Super-resolution
The progress on Hyperspectral image (HSI) super-resolution (SR) is still lagging behind the research of RGB image SR. HSIs usually have a high number of spectral bands, so accurately modeling spectral band interaction fo…
Data AugmentationHyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionEigenSR: Eigenimage-Bridged Pre-Trained RGB Learners for Single Hyperspectral Image Super-Resolution
Single hyperspectral image super-resolution (single-HSI-SR) aims to improve the resolution of a single input low-resolution HSI. Due to the bottleneck of data scarcity, the development of single-HSI-SR lags far behind th…
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionUnmixingSR: Material-aware Network with Unsupervised Unmixing as Auxiliary Task for Hyperspectral Image Super-resolution
Deep learning-based (DL-based) hyperspectral image (HIS) super-resolution (SR) methods have achieved remarkable performance and attracted attention in industry and academia. Nonetheless, most current methods explored and…
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionDeep unfolding Network for Hyperspectral Image Super-Resolution with Automatic Exposure Correction
In recent years, the fusion of high spatial resolution multispectral image (HR-MSI) and low spatial resolution hyperspectral image (LR-HSI) has been recognized as an effective method for HSI super-resolution (HSI-SR). Ho…
Exposure CorrectionHyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionCross-Scope Spatial-Spectral Information Aggregation for Hyperspectral Image Super-Resolution
Hyperspectral image super-resolution has attained widespread prominence to enhance the spatial resolution of hyperspectral images. However, convolution-based methods have encountered challenges in harnessing the global s…
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionA Spectral Diffusion Prior for Hyperspectral Image Super-Resolution
Fusion-based hyperspectral image (HSI) super-resolution aims to produce a high-spatial-resolution HSI by fusing a low-spatial-resolution HSI and a high-spatial-resolution multispectral image. Such a HSI super-resolution …
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionESSAformer: Efficient Transformer for Hyperspectral Image Super-resolution
Single hyperspectral image super-resolution (single-HSI-SR) aims to restore a high-resolution hyperspectral image from a low-resolution observation. However, the prevailing CNN-based approaches have shown limitations in …
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionHyperspectral Image Super-Resolution via Dual-domain Network Based on Hybrid Convolution
Since the number of incident energies is limited, it is difficult to directly acquire hyperspectral images (HSI) with high spatial resolution. Considering the high dimensionality and correlation of HSI, super-resolution …
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionHyperspectral Image Super Resolution with Real Unaligned RGB Guidance
Fusion-based hyperspectral image (HSI) super-resolution has become increasingly prevalent for its capability to integrate high-frequency spatial information from the paired high-resolution (HR) RGB reference image. Howev…
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-Resolution