Hyperspectral Reconstruction of Skin Through Fusion of Scattering Transform Features

Wojciech Czaja, Jeremiah Emidih, Brandon Kolstoe, Richard G. Spencer
4/15/2024
eess.IVcs.LG

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Abstract

Hyperspectral imagery (HSI) is an established technique with an array of applications, but its use is limited due to both practical and technical issues associated with spectral devices. The goal of the ICASSP 2024 'Hyper-Skin' Challenge is to extract skin HSI from matching RGB images and an infrared band. To address this problem we propose a model using features of the scattering transform - a type of convolutional neural network with predefined filters. Our model matches and inverts those features, rather than the pixel values, reducing the complexity of matching while grouping similar features together, resulting in an improved learning process.

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Cite this paper

@article{czaja2024hyperspectral,
  title  = {Hyperspectral Reconstruction of Skin Through Fusion of Scattering Transform Features},
  author = {Wojciech Czaja and Jeremiah Emidih and Brandon Kolstoe and Richard G. Spencer},
  year   = {2024},
  eprint = {2404.10030},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.10030v1}
}

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