Hyperspectral Reconstruction of Skin Through Fusion of Scattering Transform Features

• URL: http://arxiv.org/abs/2404.10030v1
• Date: Mon, 15 Apr 2024 13:34:27 GMT
• Title: Hyperspectral Reconstruction of Skin Through Fusion of Scattering Transform Features
• Authors: Wojciech Czaja, Jeremiah Emidih, Brandon Kolstoe, Richard G. Spencer,
• Abstract summary: ICASSP 2024 'Hyper-Skin' Challenge is to extract skin HSI from matching RGB images and an infrared band. Our model matches and inverts those features, rather than the pixel values, reducing the complexity of matching.
• Score: 2.180368095276185
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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