Hyperspectral Reconstruction of Skin Through Fusion of Scattering
  Transform Features
Wojciech Czaja Jeremiah Emidih Brandon Kolstoe Richard G. Spencer
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.