Spectral Super-Resolution
5 papers with code • 0 benchmarks • 0 datasets
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Libraries
Use these libraries to find Spectral Super-Resolution models and implementationsMost implemented papers
MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction
Existing leading methods for spectral reconstruction (SR) focus on designing deeper or wider convolutional neural networks (CNNs) to learn the end-to-end mapping from the RGB image to its hyperspectral image (HSI).
Learned Spectral Super-Resolution
We describe a novel method for blind, single-image spectral super-resolution.
An efficient CNN for spectral reconstruction from RGB images
Recently, the example-based single image spectral reconstruction from RGB images task, aka, spectral super-resolution was approached by means of deep learning by Galliani et al.
HPRN: Holistic Prior-embedded Relation Network for Spectral Super-Resolution
Spectral super-resolution (SSR) refers to the hyperspectral image (HSI) recovery from an RGB counterpart.
Frequency Estimation Using Complex-Valued Shifted Window Transformer
josiahwsmith10/spectral-super-resolution-swin
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In this letter, we introduce 1-D real-valued and complex-valued shifted window (Swin) transformers, referred to as SwinFreq and CVSwinFreq, respectively, for line-spectra frequency estimation on 1-D complex-valued signals.
