2-D wavelet segmentation in 3-D T-ray tomography

In this letter, segmentation techniques for terahertz (T-ray) computed tomographic (CT) imaging [1] are investigated. A set of linear image fusion and novel wavelet scale correlation segmentation techniques is adopted to achieve material discrimination within a 3-D object. The methods are applied to a T-ray CT image dataset taken from a plastic vial containing a plastic tube. This setup simulates the imaging of a simple nested organic structure, which provides an indication of the potential for using T-ray CT imaging to achieve T-ray pulsed signal classification of heterogeneous layers.