HYPERION: Hyperspectral Penetrating-type Ellipsoidal Reconstruction for Terahertz Blind Source Separation

TL;DR

HYPERION is an unsupervised hyperspectral unmixing method for terahertz signals that uses ellipsoidal geometry to effectively separate complex, noisy mixtures without prior database knowledge.

Contribution

It introduces a novel ellipsoidal geometric approach for blind hyperspectral unmixing of penetrating-type terahertz signals, requiring minimal data assumptions.

Findings

Effective separation of noisy, complex THz mixtures

No need for prebuilt spectral databases

Demonstrated high efficacy in experiments

Abstract

Terahertz (THz) technology has been a great candidate for applications, including pharmaceutic analysis, chemical identification, and remote sensing and imaging due to its non-invasive and non-destructive properties. Among those applications, penetrating-type hyperspectral THz signals, which provide crucial material information, normally involve a noisy, complex mixture system. Additionally, the measured THz signals could be ill-conditioned due to the overlap of the material absorption peak in the measured bands. To address those issues, we consider penetrating-type signal mixtures and aim to develop a blind hyperspectral unmixing (HU) method without requiring any information from a prebuilt database. The proposed HYperspectral Penetrating-type Ellipsoidal ReconstructION (HYPERION) algorithm is unsupervised, not relying on collecting extensive data or sophisticated model training. Instead, it is developed based on elegant ellipsoidal geometry under a very mild requirement on data purity, whose excellent efficacy is experimentally demonstrated.